ML12276A489
| ML12276A489 | |
| Person / Time | |
|---|---|
| Site: | Indian Point  |
| Issue date: | 08/31/2012 |
| From: | US Dept of Energy (DOE), US Energy Information Administration (EIA) |
| To: | Atomic Safety and Licensing Board Panel |
| SECY RAS | |
| References | |
| RAS 23566, 50-247-LR, 50-286-LR, ASLBP 07-858-03-LR-BD01 | |
| Download: ML12276A489 (203) | |
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ENT000587 Submitted: October 2, 2012 Assumptions to the Annual Energy Outlook 2012 August 2012 U.S. Department of Energy www.eia.gov Washington, DC 20585
This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIAs data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies.
Contents Introduction ...............................................................................................................................................................................................................3 Macroeconomic Activity Module .........................................................................................................................................................................17 International Energy Module .................................................................................................................................................................................21 Residential Demand Module .................................................................................................................................................................................27 Commercial Demand Module ...............................................................................................................................................................................39 Industrial Demand Module ....................................................................................................................................................................................53 Transportation Demand Module ..........................................................................................................................................................................69 Electricity Market Module .....................................................................................................................................................................................91 Oil and Gas Supply Module ...................................................................................................................................................................................111 Natural Gas Transmission and Distribution Module ........................................................................................................................................127 Petroleum Market Module .....................................................................................................................................................................................135 Coal Market Module................................................................................................................................................................................................151 Renewables Fuels Module ......................................................................................................................................................................................165 Appendix A: Handling of Federal and selected State legislation and regulation in the Annual Energy Outlook ................................177 iii U.S. Energy Information Administration l Asssumptions to the Annual Energy Outlook 2012
This page intentionally left blank Introduction THIS PAGE INTENTIONALLY LEFT BLANK Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2012 [1] (AEO2012), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most signi"cant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2].
The National Energy Modeling System The projections in AEO2012 are generated using the NEMS, developed and maintained by the Office of Energy Analysis (OEA) of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric Power Research Institute, Duke University, Georgia Institute of Technology, and OnLocation, Incorporated. In addition, the AEO projections are used by analysts and planners in other government agencies and nongovernment organizations.
The projections in NEMS are developed with the use of a market-based approach, subject to regulations and standards. For each fuel and consuming sector, NEMS balances energy supply and demand, accounting for economic competition among the various energy fuels and sources. The time horizon of NEMS is approximately 25 years, extending to 2035, the period in which the structure of the economy and the nature of energy markets are sufficiently understood that it is possible to represent considerable structural and regional detail. Because of the diverse nature of energy supply, demand, and conversion in the United States, NEMS supports regional modeling and analysis in order to represent the regional differences in energy markets, to provide policy impacts at the regional level, and to portray transportation "ows. To represent regional differences in energy markets, the component modules of NEMS function at the regional level: the nine Census divisions for the end-use demand modules; production regions speci"c to oil, natural gas, and coal supply and distribution; 22 regions and subregions of the North American Electric Reliability Corporation for electricity; and the "ve Petroleum Administration for Defense Districts (PADDs) for re"neries. Maps illustrating the regional formats used in each module are included in this report. Only selected regional results are presented in AEO2012, which predominant focuses on the national results. Complete regional and detailed results are available on the EIA Analyses and Projections Home Page (www.eia.gov/analysis/).
NEMS is organized and implemented as a modular system (Figure 1). The modules represent each of the fuel supply markets, conversion sectors, and end-use consumption sectors of the energy system. The modular design also permits the use of the methodology and level of detail most appropriate for each energy sector. NEMS executes each of the component modules to solve for prices of energy delivered to end users and the quantities consumed, by product, region, and sector. The delivered fuel prices encompass all the activities necessary to produce, import, and transport fuels to end users. The information "ows also include other data on such areas as economic activity, domestic production, and international petroleum supply. NEMS calls each supply, conversion, and end-use demand module in sequence until the delivered prices of energy and the quantities demanded have converged within tolerance, thus achieving an economic equilibrium of supply and demand in the consuming sectors. A solution is reached annually through the projection horizon. Other variables, such as petroleum product imports, crude oil imports, and several macroeconomic indicators, also are evaluated for convergence. Each NEMS component represents the impacts and costs of legislation and environmental regulations that affect that sector. NEMS accounts for all combustion-related carbon dioxide (CO2) emissions, as well as emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), and mercury from the electricity generation sector.
The integrating module of NEMS controls the execution of each of the component modules. To facilitate modularity, the components do not pass information to each other directly but communicate through a central data storage location. This modular design provides the capability to execute modules individually, thus allowing decentralized development of the system and independent analysis and testing of individual modules. This modularity allows use of the methodology and level of detail most appropriate for each energy sector. NEMS solves by calling each supply, conversion, and end-use demand module in sequence until the delivered prices of energy and the quantities demanded have converged within tolerance, thus achieving an economic equilibrium of supply and demand in the consuming sectors. Solution is reached annually through the projection horizon. Other variables are also evaluated for convergence such as petroleum product imports, crude oil imports, and several macroeconomic indicators.
The version of NEMS used for AEO2012 generally represents current legislation and environmental regulations, including recent government actions, for which implementing regulations were available as of December 31, 2011, such as: the Mercury and Air Toxics Standards (MATS) [3] issued by the U.S. Environmental Protection Agency (EPA) in December 2011; the Cross-State Air Pollution Rule (CSAPR) [4] as "nalized by the EPA in July 2011; the new fuel efficiency standards for medium- and heavy-duty U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 3
Introduction vehicles (HDVs) published by the EPA and the National Highway Traffic Safety Administration (NHTSA) in September 2011 [5];
Californias cap-and-trade program authorized by Assembly Bill (AB) 32, the Global Warming Solutions Act of 2006 [6]; the EPA policy memo regarding compliance of surface coal mining operations in Appalachia [7], issued on July 21, 2011; and the American Recovery and Reinvestment Act (ARRA) [8], which was enacted in mid-February 2009.
The potential impacts of proposed Federal and State legislation, regulations, or standardsor of sections of legislation that have been enacted but require funds or implementing regulations that have not been provided or speci"edare not re"ected in NEMS. However, many pending provisions are examined in alternative cases included in AEO2012 or in other analyses completed by EIA. A list of the speci"c Federal and selected State legislation and regulations included in the AEO, including how they are incorporated, is provided in Appendix A.
Figure 1. National Energy Modeling System Source: U.S. Energy Information Administration, Office of Energy Analysis.
Component Modules The component modules of NEMS represent the individual supply, demand, and conversion sectors of domestic energy markets and also include international and macroeconomic modules. In general, the modules interact through values representing prices or expenditures for energy delivered to the consuming sectors and the quantities of end-use energy consumption. This section provides brief summaries of each of the modules.
4 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Introduction Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) provides a set of macroeconomic drivers to the energy modules and receives energy-related indicators from the NEMS energy components as part of the macroeconomic feedback mechanism within NEMS. Key macroeconomic variables used in the energy modules include gross domestic product (GDP), disposable income, value of industrial shipments, new housing starts, sales of new light-duty vehicles (LDVs), interest rates, and employment.
Key energy indicators fed back to the MAM include aggregate energy prices and costs. The MAM uses the following models from IHS Global Insight: Macroeconomic Model of the U.S. Economy, National Industry Model, and National Employment Model. In addition, EIA has constructed a Regional Economic and Industry Model to project regional economic drivers, and a Commercial Floorspace Model to project 13 "oorspace types in 9 Census divisions. The accounting framework for industrial value of shipments uses the North American Industry Classi"cation System (NAICS).
International Energy Module The International Energy Module (IEM) uses assumptions of economic growth and expectations of future U.S. and world petroleum liquids production and consumption, by year, to project the interaction of U.S. and international liquids markets.
The IEM computes world oil prices, provides a world crude-like liquids supply curve, generates a worldwide oil supply/
demand balance for each year of the projection period, and computes initial estimates of crude oil and light and heavy petroleum product imports to the United States by PADD regions. The supply-curve calculations are based on historical market data and a world oil supply/demand balance, which is developed from reduced-form models of international liquids supply and demand, current investment trends in exploration and development, and long-term resource economics by country and territory. The oil production estimates include both conventional and unconventional supply recovery technologies.
In interacting with the rest of NEMS, the IEM changes the oil pricewhich is de"ned as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma (PADD 2)in response to changes in expected production and consumption of crude oil and product liquids in the United States.
Residential and Commercial Demand Modules The Residential Demand Module projects energy consumption in the residential sector by housing type and end use, based on delivered energy prices, the menu of equipment available, the availability and cost of renewable sources of energy, and housing starts. The Commercial Demand Module projects energy consumption in the commercial sector by building type and non-building uses of energy and by category of end use, based on delivered prices of energy, availability of renewable sources of energy, and macroeconomic variables representing interest rates and "oorspace construction.
Both modules estimate the equipment stock for the major end-use services, incorporating assessments of advanced technologies, including representations of renewable energy technologies, and the effects of both building shell and appliance standards, including the 2009 and 2010 consensus agreements reached between manufacturers and environmental interest groups. The Commercial Demand Module incorporates combined heat and power (CHP) technology. The modules also include projections of distributed generation (DG). Both modules incorporate changes to normal heating and cooling degree-days by Census division, based on a 10-year average and on State-level population projections. The Residential Demand Module projects an increase in the average square footage of both new construction and existing structures, based on trends in new construction and remodeling.
Industrial Demand Module The Industrial Demand Module (IDM) projects the consumption of energy for heat and power, as well as the consumption of feedstocks and raw materials, in each of 21 industry groups, subject to the delivered prices of energy and macroeconomic estimates of employment and the value of shipments for each industry. As noted in the description of the MAM, the representation of industrial activity in NEMS is based on the NAICS. The industries are classi"ed into three groups energy-intensive manufacturing, non-energy-intensive manufacturing, and nonmanufacturing. Of the eight energy-intensive manufacturing industries, seven are modeled in the IDM, including energy-consuming components for boiler/steam/
cogeneration, buildings, and process/assembly use of energy. Energy demand for petroleum re"ning (the eighth energy-intensive manufacturing industry) is modeled in the Petroleum Market Module (PMM), as described below, but the projected consumption is reported under the industrial totals.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 5
Introduction There are several updates and upgrades in the representations of select industries. The base year for the bulk chemical industry has been updated to 2006 in keeping with updates to EIAs 2006 Manufacturing Energy Consumption Survey (MECS) [10].
AEO2012 also includes an upgraded representation for the cement and lime industries and agriculture. Instead of assuming that technological development for a particular process occurs on a predetermined (exogenous) path based on engineering judgment, these upgrades allow IDM technological change to be modeled endogenously, while using more detailed process representation.
The upgrade allows for technological change, and therefore energy intensity, to respond to economic, regulatory, and other conditions. For subsequent AEOs, other industries represented in the IDM projections will be similarly upgraded.
A generalized representation of CHP is included. A revised methodology for CHP systems, implemented for AEO2012, simulates the utilization of installed CHP systems based on historical utilization rates and is driven by end-use electricity demand. To evaluate the economic bene"ts of additional CHP capacity, the model also includes an updated appraisal incorporating historical rather than assumed capacity factors and regional acceptance rates for new CHP facilities. The evaluation of CHP systems still uses a discount rate, which is equal to the projected 10-year Treasury bill rate plus a risk premium.
Transportation Demand Module The Transportation Demand Module projects consumption of energy in the transportation sector including petroleum products, electricity, methanol, ethanol, compressed natural gas, and hydrogen by transportation mode, subject to delivered energy prices and macroeconomic variables such as disposable personal income, GDP, population, interest rates, and industrial shipments. The Transportation Demand Module includes legislation and regulations, such as the Energy Policy Act of 2005, the Energy Improvement and Extension Act of 2008, and the American Recovery and Reinvestment Act of 2009, which contain tax credits for the purchase of alternatively fueled vehicles. Fleet vehicles are also modeled, allowing for analysis of legislative proposals speci"c to those markets. Representations of LDV Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) emissions standards, HDV fuel consumption and greenhouse gas emissions standards, and biofuels consumption in the module re"ect standards enacted by NHTSA and the EPA, as well as provisions in the Energy Independence and Security Act of 2007 (EISA2007).
The air transportation component of the Transportation Demand Module explicitly represents air travel in domestic and foreign markets and includes the industry practice of parking aircraft in both domestic and international markets to reduce operating costs, as well as the movement of aging aircraft from passenger to cargo markets. For passenger travel and air freight shipments, the module represents regional fuel use in regional, narrow-body, and wide-body aircraft. An infrastructure constraint, which is also modeled, can potentially limit overall growth in passenger and freight air travel to levels commensurate with industry-projected infrastructure expansion and capacity growth.
Electricity Market Module There are three primary submodules of the Electricity Market Module: capacity planning, fuel dispatching, and "nance and pricing.
The capacity expansion submodule uses the stock of existing generation capacity, the cost and performance of future generation capacity, expected fuel prices, expected "nancial parameters, expected electricity demand, and expected environmental regulations to project the optimal mix of new generation capacity that should be added in future years. The fuel dispatching submodule uses the existing stock of generation equipment types, their operation and maintenance costs and performance, fuel prices to the electricity sector, electricity demand, and all applicable environmental regulations to determine the least-cost way to meet that demand. The submodule also determines transmission and pricing of electricity. The "nance and pricing submodule uses capital costs, fuel costs, macroeconomic parameters, environmental regulations, and load shapes to estimate generation costs for each technology.
All speci"cally identi"ed options promulgated by the EPA for compliance with the Clean Air Act Amendments of 1990 (CAAA90) are explicitly represented in the capacity expansion and dispatch decisions. All "nancial incentives for power generation expansion and dispatch speci"cally identi"ed in EPACT2005 have been implemented. Several States, primarily in the Northeast, have enacted air emission regulations for CO2 that affect the electricity generation sector, and those regulations are represented in AEO2012. The AEO2012 Reference case also imposes a limit on power sector CO2 emissions for plants serving California, to represent the power sector impacts of Californias AB 32. The AEO2012 Reference case re"ects the CSAPR as "nalized by the EPA on July 6, 2011, requiring reductions in emissions from power plants that contribute to ozone and "ne particle pollution in 28 States. Reductions in mercury emissions from coal- and oil-"red power plants also are re"ected through the inclusion of the Mercury and Air Toxics Standards for power plants, "nalized by the EPA on December 16, 2011.
Although currently there is no Federal legislation in place that restricts GHG emissions, regulators and the investment community have continued to push energy companies to invest in technologies that are less GHG-intensive. The trend is captured in the AEO2012 Reference case through a 3-percentage-point increase in the cost of capital when evaluating investments in new coal-
"red power plants and new coal-to-liquids (CTL) plants without carbon capture and storage (CCS) and for pollution control retro"ts.
6 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Introduction Oil and Gas Supply Module The Oil and Gas Supply Module represents domestic crude oil and natural gas supply within an integrated framework that captures the interrelationships among the various sources of supplyonshore, offshore, and Alaskaby all production techniques, including natural gas recovery from coalbeds and low-permeability formations of sandstone and shale. The framework analyzes cash "ow and pro"tability to compute investment and drilling for each of the supply sources, based on the prices for crude oil and natural gas, the domestic recoverable resource base, and the state of technology. Oil and natural gas production activities are modeled for 12 supply regions, including 6 onshore, 3 offshore, and 3 Alaskan regions.
The Onshore Lower 48 Oil and Gas Supply Submodule evaluates the economics of future exploration and development projects for crude oil and natural gas at the play level. Crude oil resources include conventional resources as well as highly fractured continuous zones, such as the Austin chalk and Bakken shale formations. Production potential from advanced secondary recovery techniques (such as in"ll drilling, horizontal continuity, and horizontal pro"le) and enhanced oil recovery (such as CO2 "ooding, steam "ooding, polymer "ooding, and pro"le modi"cation) are explicitly represented. Natural gas resources include high-permeability carbonate and sandstone, tight gas, shale gas, and coalbed methane.
Domestic crude oil production quantities are used as inputs to the PMM in NEMS for conversion and blending into re"ned petroleum products. Supply curves for natural gas are used as inputs to the Natural Gas Transmission and Distribution Module (NGTDM) for determining natural gas wellhead prices and domestic production.
Natural Gas Transmission and Distribution Module The NGTDM represents the transmission, distribution, and pricing of natural gas, subject to end-use demand for natural gas and the availability of domestic natural gas and natural gas traded on the international market. The module tracks the "ows of natural gas and determines the associated capacity expansion requirements in an aggregate pipeline network, connecting the domestic and foreign supply regions with 12 lower 48 U.S. demand regions. The 12 lower 48 regions align with the 9 Census divisions, with three subdivided, and Alaska handled separately. The "ow of natural gas is determined for both a peak and an off-peak period in the year, assuming a historically based seasonal distribution of natural gas demand. Key components of pipeline and distributor tariffs are included in separate pricing algorithms. An algorithm is included to project the addition of compressed natural gas retail fueling capability. The module also accounts for foreign sources of natural gas, including pipeline imports and exports to Canada and Mexico, as well as lique"ed natural gas (LNG) imports and exports. For AEO2012, LNG exports and re-exports were set exogenously and assumed to reach and maintain a total level of 903 billion cubic feet per year by 2020.
Petroleum Market Module The PMM projects prices of petroleum products, crude oil and product import activity, and domestic re"nery operations, subject to demand for petroleum products, availability and price of imported petroleum, and domestic production of crude oil, natural gas liquids, and biofuelsethanol, biodiesel, biomass-to-liquids (BTL), CTL, and gas-to-liquids (GTL). Costs, performance, and "rst dates of commercial availability for the advanced alternative liquids technologies [12] are reviewed and updated annually.
The module represents re"ning activities in the "ve PADDs, as well as a lessdetailed representation of re"ning activities in the rest of the world. It models the costs of automotive fuels, such as conventional and reformulated gasoline, and includes production of biofuels for blending in gasoline and diesel. Fuel ethanol and biodiesel are included in the PMM, because they are commonly blended into petroleum products. The module allows ethanol blending into gasoline at 10 percent or less by volume (E10), 15 percent by volume (E15) in States that lack explicit language capping ethanol volume or oxygen content, and up to 85 percent by volume (E85) for use in "ex-fuel vehicles.
The PMM includes representation of the Renewable Fuels Standard (RFS) included in EISA2007, which mandates the use of 36 billion gallons of ethanol equivalent renewable fuel annually by 2022. Both domestic and imported ethanol count toward the RFS.
Domestic ethanol production is modeled for three feedstock categories: corn, cellulosic plant materials, and advanced feedstock materials. Starch-based ethanol plants are numerous (more than 190 are now in operation, with a total maximum sustainable nameplate capacity of more than 14 billion gallons annually), and they are based on a well-known technology that converts starch and sugar into ethanol. Ethanol from cellulosic sources is a new technology with only a few small pilot plants in operation. Ethanol from advanced feedstocksde"ned as plants that ferment and distill grains other than corn and reduce GHG emissions by at least 50 percentis also a new technology modeled in the PMM.
Fuels produced by Fischer-Tropsch synthesis and through a pyrolysis process are also modeled in the PMM, based on their economics relative to competing feedstocks and products. The "ve processes modeled are CTL, GTL, BTL, and pyrolysis U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 7
Introduction Coal Market Module The Coal Market Module (CMM) simulates mining, transportation, and pricing of coal, subject to end-use demand for coal differentiated by heat and sulfur content. U.S. coal production is represented in the CMM by 41 separate supply curves differentiated by region, mine type, coal rank, and sulfur content. The coal supply curves respond to capacity utilization of mines, mining capacity, labor productivity, and factor input costs (mining equipment, mining labor, and fuel requirements).
Projections of U.S. coal distribution are determined by minimizing the cost of coal supplied, given coal demands by region and sector, environmental restrictions, and accounting for minemouth prices, transportation costs, and coal supply contracts. Over the projection horizon, coal transportation costs in the CMM vary in response to changes in the cost of rail investments.
The CMM produces projections of U.S. steam and metallurgical coal exports and imports in the context of world coal trade, determining the pattern of world coal trade "ows that minimizes production and transportation costs while meeting a speci"ed set of regional world coal import demands, subject to constraints on export capacities and trade "ows. The international coal market component of the module computes trade in 3 types of coal for 17 export regions and 20 import regions. U.S. coal production and distribution are computed for 14 supply regions and 16 demand regions.
Renewable Fuels Module The Renewable Fuels Module (RFM) includes submodules representing renewable resource supply and technology input information for central-station, grid-connected electricity generation technologies, including conventional hydroelectricity, biomass (dedicated biomass plants and co-"ring in existing coal plants), geothermal, land"ll gas, solar thermal electricity, solar photovoltaics (PV), and both onshore and offshore wind energy. The RFM contains renewable resource supply estimates representing the regional opportunities for renewable energy development. Investment tax credits (ITCs) for renewable fuels are incorporated, as currently enacted, including a permanent 10-percent ITC for business investment in solar energy (thermal nonpower uses as well as power uses) and geothermal power (available only to those projects not accepting the production tax credit [PTC] for geothermal power). In addition, the module re"ects the increase in the ITC to 30 percent for solar energy systems installed before January 1, 2017. The extension of the credit to individual homeowners under EIEA2008 is re"ected in the Residential and Commercial Demand Modules.
PTCs for wind, geothermal, land"ll gas, and some types of hydroelectric and biomass-fueled plants also are represented. They provide a credit of up to 2.2 cents per kilowatthour for electricity produced in the "rst 10 years of plant operation. For AEO2012, new wind plants coming on line before January 1, 2013, are eligible to receive the PTC; other eligible plants must be in service before January 1, 2014. As part of the ARRA, plants eligible for the PTC may instead elect to receive a 30-percent ITC or an equivalent direct grant. AEO2012 also accounts for new renewable energy capacity resulting from State renewable portfolio standard (RPS) programs, mandates, and goals.
Cases for the Annual Energy Outlook 2012 In preparing projections for AEO2012, EIA evaluated a wide range of trends and issues that could have major implications for U.S. energy markets between now and 2035. Besides the Reference case, AEO2012 presents detailed results for "ve alternative cases that differ from each other due to fundamental assumptions concerning the domestic economy and world oil market conditions. These alternative cases include the following:
Economic Growth - In the Reference case, real GDP grows at an average annual rate of 2.5 percent from 2010 through 2035, supported by a 1.9-percent-per-year growth in productivity in nonfarm business, a 1.0-percent-per-year growth in nonfarm employment, and population growth of 0.9 percent per year. In the High Economic Growth case, real GDP is projected to increase by 3.0 percent per year, with population growth of 1.0 percent per year and productivity and nonfarm employment growing at 2.2 percent and 1.2 percent per year, respectively. In the Low Economic Growth case, the average annual growth in GDP, population, productivity, and nonfarm employment is 2.0, 0.8, 1.5 and 0.8 percent per year, respectively.
Price Cases - The oil price in AEO2012 is de"ned as the average price of light, low-sulfur crude oil delivered in Cushing, Oklahoma, and is similar to the price for light, sweet crude oil traded on the New York Mercantile Exchange, referred to as West Texas Intermediate (WTI). AEO2012 also includes a projection of the U.S. annual average re"ner acquisition cost of imported crude oil, which is more representative of the average cost of all crude oils used by domestic re"ners. The historical record shows substantial variability in oil prices, and there is arguably even more uncertainty about future prices in the long term. AEO2012 considers three oil price cases (Reference, Low Oil Price, and High Oil Price) to allow an assessment of alternative views on the future course of oil prices. The Low and High Oil Price cases re"ect a wide range of potential price paths, resulting from variation in demand by countries outside the Organization for Economic Cooperation and Development (OECD) for liquid fuels due to different levels of economic growth. The Low and High Oil Price cases also re"ect different assumptions about decisions by members of the Organization of the Petroleum Exporting Countries (OPEC) regarding the preferred rate of oil production and about the future "nding and development costs and accessibility of conventional oil resources outside the United States.
8 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Introduction
- In the Reference case, real oil prices rise from $93 per barrel (2010 dollars) in 2011 to $145 per barrel in 2035. The Reference case represents EIAs current judgment regarding exploration and development costs and accessibility of oil resources. It also assumes that OPEC producers will choose to maintain their share of the market and will schedule investments in incremental production capacity so that OPECs conventional oil production will represent about 40 percent of the worlds total liquids production over the projection period.
- In the Low Oil Price case, crude oil prices are only $62 per barrel (2010 dollars) in 2035, compared with $145 per barrel in the Reference case. In the Low Oil Price case, the low price results from lower demand for liquid fuels in the non-OECD nations. Lower demand is derived from lower economic growth relative to the Reference case. In this case, GDP growth in the non-OECD countries is reduced by 1.5 percentage points relative to Reference case in each projection year, beginning in 2015. The OECD projections are affected only by the price impact. On the supply side, OPEC countries increase their conventional oil production to obtain a 46-percent share of total world liquids production, and oil resources outside the U.S.
are more accessible and/or less costly to produce (as a result of technology advances, more attractive "scal regimes, or both) than in the Reference case.
- In the High Oil Price case, oil prices reach about $200 per barrel (2010 dollars) in 2035. In the High Oil Price case, the high prices result from higher demand for liquid fuels in the non-OECD nations. Higher demand is measured by higher economic growth relative to the Reference case. In this case, GDP growth in the non-OECD region is raised by 0.1 to 1.0 percentage point relative to the Reference case in each projection year, starting in 2012. GDP growth rates for China and India are raised by 1.0 percentage point relative to the Reference case in 2012, declining to 0.3 percentage point above the Reference case in 2035. GDP growth rates for most other non-OECD regions average about 0.5 percentage point above the Reference case in each projection year. The OECD projections are affected only by the price impact. On the supply side, OPEC countries are assumed to reduce their market share somewhat, and oil resources outside the United States are assumed to be less accessible and/or more costly to produce than in the Reference case.
In addition to these cases, 25 additional alternative cases presented in Table 1.1 explore the impact of changing key assumptions on individual sectors.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 9
Introduction Table 1.1. Summary of AEO2012 cases Case name Description Reference Baseline economic growth (2.5 percent per year from 2010 through 2035), oil price, and technology assumptions. Light, sweet crude oil prices rise to about $145 per barrel (2010 dollars) in 2035. Assumes RFS target to be met as soon as possible.
Low Economic Growth Real GDP grows at an average annual rate of 2.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case.
High Economic Growth Real GDP grows at an average annual rate of 3.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case.
Low Oil Price Low prices result from a combination of low demand for petroleum and other liquid fuels in the non-OECD nations and higher global supply. Lower demand is measured by lower economic growth relative to the Reference case. In this case, GDP growth in the non-OECD is reduced by 1.5 percentage points in each projection year relative to Reference case assumptions, beginning in 2015. On the supply side, OPEC increases its market share to 46 percent, and the costs of other liquids production technologies are lower than in the Reference case. Light, sweet crude oil prices fall to $62 per barrel in 2035.
High Oil Price High prices result from a combination of higher demand for liquid fuels in the non-OECD nations and lower global supply. Higher demand is measured by higher economic growth relative to the Reference case. In this case, GDP growth rates for China and India are raised by 1.0 percentage point relative to the Reference case in 2012 and decline to 0.3 percentage point above the Reference case in 2035. GDP growth rates for other non-OECD regions average about 0.5 percentage point above the Reference case. OPEC market share remains at about 40 percent throughout the projection, and non-OPEC conventional production expands more slowly in the short to middle term relative to the Reference case. Light, sweet crude oil prices rise to $200 per barrel (2010 dollars) in 2035.
No Sunset Begins with the Reference case and assumes extension of all existing energy policies and legislation that contain sunset provisions, except those requiring additional funding (e.g.,
loan guarantee programs) and those that involve extensive regulatory analysis, such as CAFE improvements and periodic updates of efficiency standards.
Extended Policies Begins with the No Sunset case but excludes extension of tax credits for blenders and for other biofuels that were included in the No Sunset case. Assumes expansion of the maximum industrial ITC and CHP credits and extension of the program. The case includes additional rounds of efficiency standards for residential and commercial products, as well as new standards for products not yet covered, adds multiple rounds of national building codes by 2026, and increases LDV fuel economy standards in the transportation sector through 2035.
Transportation: CAFE Standards Explores energy and market impacts assuming that LDV CAFE and greenhouse gas emissions standards proposed for model years 2017-2025 are enacted.
Transportation: High Technology Battery Explores the impact of signi"cant improvement in vehicle battery and nonbattery system cost and performance on new LDV sales, energy consumption, and GHG emissions.
Transportation: HDV Reference Incorporates revised CNG and LNG pricing assumptions and HDV market acdeptance relative to the AEO2012 Reference case.
Transportation: Using the HDV Reference case, explores energy and market issues associated with the HD NGV, Potential expansion of natural gas refueling infrastructure for the HDV market.
Electricity: Assumes that all nuclear plants are limited to a 60-year life (31 gigawatts of retirements),
Low Nuclear uprates are limited to the 1 gigawatt that has been reported to EIA, and planned additions are the same as in the Reference case.
Electricity: High Nuclear Assumes that all nuclear plants are life-extended beyond 60 years (except for one announced retirement), and uprates are the same as in the Reference case. New plants include those under construction and plants that have a scheduled NRC or Atomic Safety and Licensing Board hearing and use a currently certi"ed design (e.g., AP1000).
Electricity: Reference 05 Includes CSAPR and MATS as in the Reference case, with reduced 5-year environmental investment recovery.
Electricity: Low Gas Price 05 Includes CSAPR and MATS as in the Reference case, with reduced 5-year environmental investment recovery combined with the High Estimated Ultimate Recovery (EUR) case.
10 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Introduction Table 1.1. Summary of AEO2012 cases (cont.)
Case name Description Renewable Fuels: Low Renewable Costs for new nonhydropower renewable generating technologies start 20 percent lower in 2012 Technology Cost and decline to 40 percent lower than Reference case levels in 2035. Capital costs of renewable liquid fuel technologies start 20 percent lower in 2012 and decline to approximately 40 percent lower than Reference case levels in 2035.
Petroleum: LFMM Changes in the re"ning industry in the past and prospective future are discussed in the context of the development of the Liquids Fuels Market Module (LFMM) developed for NEMS. Provides overview of large-scale trends and highlights of speci"c issues that may require further analysis.
Oil and Gas: Low EUR Estimated ultimate recovery (EUR) per tight oil or shale gas well is 50 percent lower than in the Reference case.
Oil and Gas: High EUR EUR per tight oil and shale gas well is assumed to be 50 percent higher than in the Reference case.
Oil and Gas: High Technically The well spacing for all tight oil and shale gas plays is assumed to be 8 wells per square mile (i.e.,
Recoverable Resources (TRR) each well has an average drainage area of 80 acres) and the EUR for tight oil and shale gas wells is assumed to be 50 percent higher than in the Reference case.
Coal: Low Coal Cost Regional productivity growth rates for coal mining are approximately 2.8 percent per year higher than in the Reference case, and coal mining wages, mine equipment, and coal transportation rates in 2035 are between 21 and 25 percent lower than in the Reference case.
Coal: High Coal Cost Regional productivity growth rates for coal mining are approximately 2.8 percent per year lower than in the Reference case, and coal mining wages, mine equipment, and coal transportation rates in 2035 are between 25 and 27 higher than in the Reference case.
Integrated 2011 Demand Referred to in text as the 2011 Demand Technology. Assumes future equipment purchases in the Technology residential and commercial sectors are based only on the range of equipment available in 2011.
Energy efficiency of new industrial plant and equipment is held constant at the 2012 level over the projection period.
Integrated Best Available Assumes all future equipment purchases in the residential and commercial sectors are made from Demand Technology a menu of technologies that includes only the most efficient models available in a particular year for each fuel, regardless of cost.
Integrated High Demand Assumes earlier availability, lower costs, and higher efficiencies for more advanced residential and Technology commercial equipment. For new residential and commercial construction, building shell efficiencies are assumed to meet ENERGY STAR requirements after 2016. Industrial sector assumes earlier availability, lower costs, and higher efficiency for more advanced equipment and a more rapid rate of improvement in the recovery of biomass byproducts from industrial processes. In the transportation sector, the characteristics of conventional and alternative-fuel LDVs re"ect more optimistic assumptions about incremental improvements in fuel economy and costs. Freight trucks are assumed to see more rapid improvement in fuel efficiency for engine and emissions control technologies. More optimistic assumptions for fuel efficiency improvements are also made for the air, rail, and shipping sectors.
Integrated 2011 Technology Combination of the Integrated 2011 Demand Technology case with the assumption that costs of new power plants do not improve from 2012 levels throughout the projection.
Integrated High Technology Combination of the Integrated High Demand Technology case and the Low Renewable Technology Cost case. Also assumes that costs for new nuclear and fossil-"red power plants are lower than Reference case levels, by 20 percent in 2012 and 40 percent in 2035.
No GHG Concern No GHG emissions reduction policy is enacted, and market investment decisions are not altered in anticipation of such a policy.
GHG15 Applies a fee for CO2 emissions throughout the economy, starting at $15 in 2013 and rising by 5 percent per year through 2035. Fee is set to target the same reduction in CO2 emissions as in the AEO2011 GHG Price Economywide case.
GHG25 Applies a fee for CO2 emissions throughout the economy, starting at $25 in 2013 and rising by 5 percent per year through 2035. Fee is set at the same dollar amount as in the AEO2011 GHG Price Economywide case.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 11
Introduction Carbon dioxide emissions Carbon dioxide emissions from energy use are dependent on the carbon content of the fossil fuel, the fraction of the fuel consumed in combustion, and the consumption of that fuel. The product of the carbon content at full combustion and the combustion fraction yields an adjusted carbon emission factor for each fossil fuel. The emissions factors are expressed in millions of metric tons of carbon dioxide emitted per quadrillion Btu of energy use, or equivalently, in kilograms of carbon dioxide per million Btu. The adjusted emissions factors are multiplied by the energy consumption of the fossil fuel to arrive at the carbon dioxide emissions projections.
For fuel uses of energy, all of the carbon is assumed to be oxidized, so the combustion fraction is equal to 1.0 (in keeping with a recent change in international conventions). Previously, a small fraction of the carbon content of the fuel was assumed to remain unoxidized. The carbon in nonfuel use of energy, such as for asphalt and petrochemical feedstocks, is assumed to be sequestered in the product and not released to the atmosphere. For energy categories that are mixes of fuel and nonfuel uses, the combustion fractions are based on the proportion of fuel use. In calculating carbon dioxide emissions for motor gasoline, the direct emissions from renewable blending stock (ethanol) is omitted. Similarly, direct emissions from biodiesel are omitted from reported carbon dioxide emissions.
Any carbon dioxide emitted by biogenic renewable sources, such as biomass and alcohols, is considered balanced by the carbon dioxide sequestration that occurred in its creation. Therefore, following convention, net emissions of carbon dioxide from biogenic renewable sources are assumed to be zero in reporting energy-related carbon dioxide emissions; however, to illustrate the potential for these emissions in the absence of any offsetting sequestration, as might occur under related land use change, the carbon dioxide emissions from biogenic fuel use are calculated and reported separately.
Table 1.2 presents the assumed carbon dioxide coefficients at full combustion, the combustion fractions, and the adjusted carbon dioxide emission factors used for AEO2012.
12 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Introduction Table 1.2. Carbon dioxide emission factors million metric tons carbon dioxide equivalent per quadrillion Btu Carbon Dioxide Adjusted Coefficient at Combustion Emission Fuel Type Full Combustion Fraction Factor Petroleum Gasoline (net of ethanol) 71.26 1.0000 71.26 Lique"ed Petroleum Gas Used as Fuel 62.97 1.0000 62.97 Used as Feedstock 61.27 0.2000 12.25 Jet Fuel 70.88 1.0000 70.88 Distillate Fuel (net of biodiesel) 73.15 1.0000 73.15 Residual Fuel 78.80 1.0000 78.80 Asphalt and Road Oil 75.61 0.0000 0.00 Lubricants 74.21 0.5000 37.11 Petrochemical Feedstocks 71.02 0.3533 25.09 Kerosene 72.31 1.0000 72.31 Petroleum Coke 102.12 0.9014 92.05 Petroleum Still Gas 64.20 1.0000 64.20 Other Industrial 74.54 1.0000 74.54 Coal Residential and Commercial 95.35 1.0000 95.35 Metallurgical 93.71 1.0000 93.71 Coke 114.14 1.0000 114.14 Industrial Other 93.88 1.0000 93.98 1
Electric Utility 95.52 1.0000 95.52 Natural Gas Used as Fuel 53.06 1.0000 53.06 Used as Feedstocks 53.06 0.5270 27.96 Biogenic Energy Sources Biomass 88.45 1.0000 88.45 Biogenic Waste 90.65 1.0000 90.65 Biofuels Heats and Coproducts 88.45 1.0000 88.45 Ethanol 65.88 1.0000 65.88 Biodiesel 73.88 1.0000 73.88 Liquids from Biomass 73.15 1.0000 73.15 Green Liquids 73.15 1.0000 73.15 1
Emission factors for coal used for electricity generation are speci"ed by coal supply region and types of coal, so the average carbon dioxide content for coal varies throughout the projection. The 2009 average is 95.52.
Source: U.S. Energy Information Administration, Emissions of Greenhouse Gases in the United States 2009, DOE/EIA-0573(2009), (Washington, DC, February 2010).
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 13
Introduction Notes and sources
[1] Energy Information Administration, Annual Energy Outlook 2012 (AEO2012), DOE/EIA-0383(2012), (Washington, DC, June 2012).
[2] NEMS documentation reports are available on the EIA Homepage (www.eia.gov/analysis/model-documentation.cfm).
[3] U.S. Environmental Protection Agency, Mercury and Air Toxics Standards, website www.epa.gov/mats.
[4] U.S. Environmental Protection Agency, Cross-State Air Pollution Rule (CSAPR), website epa.gov/airtransport. CSAPR was scheduled to begin on January 1, 2012; however, the U.S. Court of Appeals for the D.C. Circuit issued a stay delaying implementation while it addresses legal challenges to the rule that have been raised by several power companies and States.
CSAPR is included in AEO2012 despite the stay, because the Court of Appeals had not made a "nal ruling at the time AEO2012 was published.
[5] U.S. Environmental Protection Agency and National Highway Traffic Safety Administration, Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles; Final Rule, Federal Register, Vol. 76, No. 179 (September 15, 2011), pp. 57106-57513, website www.gpo.gov/fdsys/pkg/FR-2011-09-15/html/2011-20740.htm.
[6] California Air Resources Board (ARB), California Cap on Greenhouse Gas Emissions and Market-Based Compliance Mechanisms, Article 5 95800 to 96023, website www.arb.ca.gov/cc/capandtrade/capandtrade.htm.
[7] U.S. Environmental Protection Agency, July 21, 2011 Final Memorandum: Improving EPA Review of Appalachian Surface Coal Mining Operations Under the Clean Water Act, National Environmental Polic Act, and the Environmental Justice Executive Order, website water.epa.gov/lawsregs/guidance/wetlands/mining.cfm.
[8] For the complete text of the American Recovery and Reinvestment Act of 2009, see website www.gpo.gov/fdsys/pkg/
PLAW-111pub15/html/PLAW-111pub15.htm.
14 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Macroeconomic Activity Module THIS PAGE INTENTIONALLY LEFT BLANK Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents interactions between the U.S. economy and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP), is a key determinant of growth in the demand for energy. Associated economic factors, such as interest rates and disposable income, strongly in"uence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also re"ected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2011), (Washington, DC, June 2011).
Key assumptions The output of the U.S. economy, measured by GDP, is expected to increase by 2.5 percent per year between 2010 and 2035 in the Reference case. Two key factors help explain the growth in GDP: the growth rate of nonfarm employment and the rate of productivity change associated with employment. As Table 2.1 indicates, in the Reference case, real GDP grows by 2.5 percent for the next ten years and by 2.6 percent for the "nal "fteen years of the projection. Both the high and low macroeconomic growth cases show roughly 0.5 percentage point differences in growth as compared to the Reference case. Non-farm employment shows higher growth in the "rst "ve years of the projection period and then returns to its long-run trend growth. In the Reference case, nonfarm employment grows by 1.0 percent from 2010 to 2035 as compared to 1.2 percent and 0.8 percent in the High Growth and Low Growth cases, respectively. In the Reference case, productivity (measured as output per hour in nonfarm businesses) grows by 1.9 percent from 2010 to 2035, showing slower growth than the 2.0-percent growth experienced during the previous 30 years. Business "xed investment as a share of nominal GDP is expected to grow over the last 10 years of the projection. The resulting growth in the capital stock and the technology base of that capital stock helps to sustain productivity growth of 1.9 percent from 2010 to 2035.
The Census Bureaus middle series population projection is used as a basis for population growth in the AEO2012. Total population is expected to grow by 0.9 percent per year between 2010 and 2035, and the share of population over 65 is expected to increase over time. However, the share of the labor force in the population over 65 is also projected to increase in the projection period.
To achieve the Reference cases long-run 2.5 percent economic growth, there is an anticipated steady growth in labor productivity. The improvement in labor productivity re"ects the positive effects of a growing capital stock as well as technological change over time. Nonfarm labor productivity is expected to remain between 1.7 and 2.2 percent for the remainder of the projection period from 2015 through 2035.
Table 2.1. Growth in gross domestic product, nonfarm employment and productivity Assumptions 2010-2015 2015-2020 2020-2035 2010-2035 Real GDP (Billion Chain-Weighted $2005)
High Growth 3.1% 2.9% 2.9% 3.0%
Reference 2.5% 2.5% 2.6% 2.5%
Low Growth 1.9% 1.8% 2.1% 2.0%
Nonfarm Employment High Growth 1.9% 1.1% 0.9% 1.2%
Reference 1.4% 1.1% 0.8% 1.0%
Low Growth 1.3% 0.9% 0.6% 0.8%
Productivity High Growth 1.4% 2.0% 2.4% 2.1%
Reference 1.1% 1.7% 2.2% 1.9%
Low Growth 0.8% 1.2% 1.7% 1.4%
Source: U.S. Energy Information Administration, AEO2012 National Energy Modeling system runs: AEO2012.d020112C, LM2012.d022412A, and HM2012.
d022412A.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 17
Macroeconomic Activity Module To re"ect uncertainty in the projection of U.S. economic growth, the AEO2012 uses High and Low Economic Growth cases to project the possible impacts of alternative economic growth assumptions on energy markets. The High Economic Growth case incorporates higher population, labor force and productivity growth rates than the Reference case. Due to the higher productivity gains, in"ation and interest rates are lower as compared to the Reference case. Investment, disposable income and industrial production are greater. Economic output is projected to increase by 3.0 percent per year between 2010 and 2035. The Low Economic Growth case assumes lower population, labor force, and productivity gains, with resulting higher prices and interest rates and lower industrial output growth. In the Low Economic Growth case, economic output is expected to increase by 2.0 percent per year over the projection horizon.
18 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
International Energy Module THIS PAGE INTENTIONALLY LEFT BLANK International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply-demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region.
Changes in the oil price (WTI), which is de"ned as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in PADD2, are computed in response to:
- 1. The difference between projected U.S. total crude-like liquids production and the expected U.S. total crude-like liquids production at the current oil price (estimated using the current oil price and the exogenous U.S. total crude-like liquids supply curve for each year).
and
- 2. The difference between projected U.S. total crude-like liquids consumption and the expected U.S. total crude-like liquids consumption at the current oil price (estimated using the current oil price and the exogenous U.S. total crude-like liquids demand curve).
Key assumptions The level of oil production by OPEC is a key factor in"uencing the oil price projections incorporated into AEO2012. Non-OPEC production, worldwide regional economic growth rates and the associated regional demand for oil are additional factors affecting the world oil price.
For the low, reference, and high oil price cases, the oil price reaches $62, $145 and $200 per barrel, respectively, in 2010 dollars. The Reference case assumes that OPEC producers will continue to demonstrate a disciplined production approach.
The Reference case represents EIAs current judgment regarding exploration and development costs and accessibility of oil resources outside United States. It also assumes that OPEC producers will choose to maintain their share of the market of about 42 percent of the worlds total liquids production. In the Low Oil Price case, the low price results from lower demand for liquid fuels in the non-OECD nations. In this case, GDP growth in the non-OECD is reduced by 1.5 percentage points in each projection year beginning in 2015 relative to Reference case. On the supply side, OPEC countries increase their conventional oil production to obtain a 46 percent share of total world liquids production, and oil resources outside the United States are more accessible and/or less costly to produce than in the Reference case. In the High Oil Price case, the high prices result from higher demand for liquid fuels in the non-OECD nations. Higher demand is measured by higher economic growth relative to the Reference case.
In this case, GDP growth in the non-OECD region is raised by 0.1 to 1.0 percentage points relative to Reference case in each projection year, starting in 2012. China and India GDP growth rates are raised by 1.0 percentage points relative to the Reference case in 2012 and decline to 0.3 percentage points above the Reference case in 2035. GDP growth rates for most other non-OECD regions average about 0.5 percentage points above the Reference case in each projection year. On the supply side, OPEC countries are assumed to reduce their market share somewhat, and oil resources outside the United States are assumed to be less accessible and/or more costly to produce than in the Reference case.
OPEC oil production in the Reference case is assumed to increase throughout the projection (Figure 3), at a rate that enables the organization to maintain an approximately constant market share over the projection period. OPEC is assumed to be an important source of additional production because its member nations hold a major portion of the worlds total reserves exceeding 1060 billion barrels, about 72 percent of the worlds estimated total, at the beginning of 2011. [1] Despite investment from foreign sources, Iraqs oil production is not assumed to maintain steady growth until after 2015 as infrastructure limitations as well as security and legislative issues are assumed to slow development for the next "ve years.
Non-U.S., non-OPEC oil production projections in the AEO2012 are developed in two stages. Projections of liquids production before 2015 are based largely on a project-by-project assessment of major "elds, including volumes and expected schedules, with consideration given to the decline rates of active projects, planned exploration and development activity, and country-speci"c geopolitical situations and "scal regimes. Incremental production estimates from existing and new "elds after 2015 are estimated based on country-speci"c consideration of economics and ultimate technically recoverable resource estimates. The non-OPEC production path for the Reference case is shown in Figure 4.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 21
International Energy Module
2009 dollars per barrel Source: U.S. Energy Information Administration. AEO2012, National Energy Modeling System runs REF2012.
d020112C, HP2012.d022112A LP2012.d022112A.
!" " # " "$%&
million barrels per day 50 History Projections 40 30 20 10 0
1995 2000 2005 2010 2015 2020 2025 2030 2035 OPEC = Organization of Petroleum Exporting Countries.
Source: U.S. Energy Information Administration. AEO2012 National Energy Modeling Sysytem run REF2012.
d020112C.
22 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
International Energy Module
'* !" " # " "$%&
million barrels per day 70 History Projections 60 50 40 30 20 10 0
1995 2000 2005 2010 2015 2020 2025 2030 2035 OPEC = Organization of Petroleum Exporting Countries.
Source: U.S. Energy Information Administion. AEO2012 National Energiy Modeling System run REF2012.
d020112C.
The non-U.S. oil production projections in the AEO2012 are limited by country-level assumptions regarding technically recoverable oil resources. Inputs to these resource estimates include the USGS World Petroleum Assessment of 2000 and oil reserves published in the Oil & Gas Journal by PennWell Publishing Company, a summary of which is shown in Table 3.1.
The Reference case growth rates for GDP for various regions in the world are shown in Table 3.2. The GDP growth rate assumptions for non-U.S. countries/regions are taken from IHS Global Insight, Inc., Global detailed forecast (August 25, 2011).
The values for growth in total liquids demand in the International Energy Module, which depend upon the oil price levels as well as GDP growth rates, are shown in Table 3.3 for the Reference case by regions.
+- / &34
billion barrels Region Proved Oil Reserves Western Hemisphere 441.9 Western Europe 11.0 Asia-Paci"c 40.3 Eastern Europe and Former Soviet Union (F.S.U.) 100.0 Middle East 752.9 Africa 123.6 Total World 1,469.6 Total OPEC 1,064.8 Source: Pennwell Corporation, Oil and Gas Journal, Vol 109. 19 (Dec. 5, 2011).
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 23
International Energy Module
+- 5 6" "" 7
2005 purchasing power parity weights and prices Region Average Annual Percentage Change OECD 2.10%
OECD Americas 2.58%
OECD Europe 1.81%
OECD Asia 1.40%
Non-OECD 4.70%
Non-OECD Europe and Eurasia 2.79%
Non-OECD Asia 5.46%
Middle East 3.80%
Africa 3.85%
Central and South America 3.83%
Total World 3.46%
Source: U.S. Energy Information Administration, National Energy Modeling System run REF2012.d0201C.
+- 5 /"$"& " " #6"$%& 7
billion barrels Region Oil Demand Growth OECD 0.03%
OECD Americas 0.18%
OECD Europe -0.20%
OECD Asia -0.02%
Non-OECD 1.86%
Non-OECD Europe and Eurasia 0.46%
Non-OECD Asia 2.64%
Middle East 1.34%
Africa 0.92%
Central and South America 1.30%
Total World 0.94%
Source: U.S. Energy Information Administration, National Energy Modeling System run REF2012.D0201C; and World Energy Projection system Plus (2012), run AEO2012-REFA_annual_1236.
Notes and sources
[1] PennWell Corporation, Oil and Gas Journal, Vol. 109.19 (December 5, 2011).
24 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Residential Demand Module THIS PAGE INTENTIONALLY LEFT BLANK Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the unit energy consumption (UEC) by appliance (in million Btu per household per year).
The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and by Census Division, and prices for each energy source for each of the nine Census Divisions (see Figure 5).
The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or State efficiency standards. As energy prices and available equipment change over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.
Figure 5. United States Census Divisions AK West North East Mountain Central WA North MT ND MN Central VT ME New OR England WI SD NH MA ID WY MI NY CA IA RI NE CT NV Pacific PA UT OH NJ IN CO KS MO IL Middle Atlantic DE WV VA AZ NM East South Central KY MD NC OK TN SC AR South Atlantic TX HI AL GA LA MS West South FL Central Pacific Middle Atlantic West South Central New England East South Central East North Central South Atlantic West North Central Mountain Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 27
Residential Demand Module The end-use services for which equipment stocks are modeled include space conditioning (heating and cooling), water heating, refrigeration, freezers, dishwashers, clothes washers, lighting, furnace fans, color televisions, personal computers, cooking, clothes drying, ceiling fans, coffee makers, spas, home security systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, dehumidi"ers, external power supplies, and VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric appliances. The modules output includes number of households, equipment stock, average equipment efficiencies, and energy consumed by service, fuel, and geographic location. The fuels represented are distillate fuel oil, lique"ed petroleum gas, natural gas, kerosene, electricity, wood, coal, geothermal, and solar energy.
One of the implicit assumptions embodied in the Residential Demand Module is that, through 2035, there will be no radical changes in technology or consumer behavior. With the exception of efficiency levels described in consensus agreements among equipment manufacturers and efficiency advocates, no new regulations of efficiency beyond those currently embodied in law or new government programs fostering efficiency improvements are assumed. Technologies which have not gained widespread acceptance today will generally not achieve signi"cant penetration by 2035. Currently available technologies will evolve in both efficiency and cost. In general, at the same efficiency level, future technologies will be less expensive, in real dollar terms, than those available today. When choosing new or replacement technologies, consumers will behave similarly to the way they now behave. The intensity of end uses will change moderately in response to price changes. Electric end uses will continue to expand, but at a decreasing rate [1].
Key assumptions Housing Stock submodule An important determinant of future energy consumption is the projected number of households. Base year estimates for 2005 are derived from the Energy Information Administrations (EIA) Residential Energy Consumption Survey (RECS) (Table 4.1). The projection for occupied households is done separately for each Census Division. It is based on the combination of the previous years surviving stock with projected housing starts provided by the NEMS Macroeconomic Activity Module. The Housing Stock submodule assumes a constant survival rate (the percentage of households which are present in the current projection year, which were also present in the preceding year) for each type of housing unit; 99.6 percent for single-family units, 99.9 percent for multifamily units, and 97.6 percent for mobile home units.
Projected fuel consumption is dependent not only on the projected number of housing units, but also on the type and geographic distribution of the houses. The intensity of space heating energy use varies greatly across the various climate zones in the United States. Also, fuel prevalence varies across the countryoil (distillate) is more frequently used as a heating fuel in the New England and Middle Atlantic Census Divisions than in the rest of the country, while natural gas dominates in the Midwest. An example of differences by housing type is the more prevalent use of lique"ed petroleum gas in mobile homes relative to other housing types.
Table 4.1. 2005 Households Census Single-Family Units Multifamily Units Mobile Homes Total Units New England 3,382,964 1,899,961 173,072 5,465,996 Middle Atlantic 10,077,231 4,794,686 254,610 15,116,527 East North Central 14,091,216 3,233,929 424,271 17,749,416 West North Central 6,107,582 1,406,214 340,759 7,854,555 South Atlantic 14,823,660 4,910,592 1,962,563 21,696,715 East South Central 5,438,660 729,591 724,503 6,892,754 West South Central 8,892,255 2,120,675 1,109,901 12,122,831 Mountain 5,680,398 951,482 922,976 7,554,856 Paci"c 11,150,078 4,456,348 1,030,541 16,636,967 United States 79,653,923 24,493,498 6,943,196 111,090,617 Source: U.S. Energy Information Administration, 2005 Residential Energy Consumption Survey.
28 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Residential Demand Module Technology Choice submodule The key inputs for the Technology Choice submodule are fuel prices by Census Division and characteristics of available equipment (installed cost, maintenance cost, efficiency, and equipment life). The Integrating Module of NEMS estimates fuel prices through an equilibrium simulation that balances supply and demand and passes the prices to the Residential submodule.
Prices combined with equipment UEC (a function of efficiency) determine the operating costs of equipment. Equipment characteristics are exogenous to the model and are modi"ed to re"ect both Federal standards and anticipated changes in the market place. Table 4.2 lists capital costs and efficiency for selected residential appliances for the years 2010 and 2020.
+- ' :" "&4" & "#6"
2020 Installed Relative 2010 Installed 2010 Cost 2020 Approximate Equipment Type Performance1 Cost (2010$)2 Efficiency3 (2010$)2 Efficiency3 Hurdle Rate Minimum $4,800 7.7 $4,950 8.0 Electric Heat Pump (heating component) Best $7,850 10.7 $8,200 10.8 25%
Minimum $2,500 0.78 $2,750 0.90 Natural Gas Furnace4 Best $2,625 0.98 $3,750 0.98 15%
Minimum $275 9.8 $295 11.0 Room Air Conditioner Best $455 12.0 $515 13.0 42%
Minimum $3,200 13.7 $3,550 14.0 Central Air Conditioner Best $4,500 21.0 $5,750 24.0 25%
Minimum $500 511 $525 408 5
Refrigerator Best $850 342 $1,250 327 10%
Minimum $600 0.90 $675 0.95 Electric Water Heater Best $1,370 2.35 $2,050 2.35 50%
Solar Water Heater6 N/A $5,320 N/A $5,110 N/A 30%
1 Minimum performance refers to the lowest-efficiency equipment available. Best refers to the highest-efficiency equipment available.
2 Installed costs are given in 2010 dollars in the original source document.
3 Efficiency measurements vary by equipment type. Electric heat pumps are based on Heating Seasonal Performance Factor (HSPF); natural gas furnaces are based on Annual Fuel Utilization Efficiency (AFUE); central air conditioners are based on Seasonal Energy Efficiency Ratio (SEER); room air conditioners are based on Energy Efficiency Ratio (EER); refrigerators are based on kilowatt-hours per year; and water heaters are based on Energy Factor (delivered Btu divided by input Btu).
4 Values are for Northern regions of U.S.
5 Re"ects refrigerator with top mounted freezer with 20.6 cubic feet nominal volume.
6 Values are for Southern regions of U.S.
Source: EIA Technology Forecast Updates, (Navigant Consulting , 2010).
Table 4.3 provides the cost and performance parameters for representative distributed generation technologies. The model also incorporates endogenous learning for the residential distributed generation technologies, allowing for declining technology costs as shipments increase. For fuel cell and photovoltaic systems, learning parameter assumptions for the Reference case result in a 13-percent reduction in capital costs each time the number of units shipped to the buildings sectors (residential and commercial) doubles. Capital costs for small wind, a relatively mature technology, only decline three percent with each doubling of shipments.
The Residential Demand Module projects equipment purchases based on a nested choice methodology. The "rst stage of the choice methodology determines the fuel and technology to be used. The equipment choices for cooling, water heating, and cooking are linked to the space heating choice for new construction. Technology and fuel choice for replacement equipment uses a nested methodology similar to that for new construction, but includes (in addition to the capital and installation costs of the equipment) explicit costs for fuel or technology switching (e.g., costs for installing gas lines if switching from electricity or oil to gas, or costs for adding ductwork if switching from electric resistance heat to central heating types). Also, for replacements, there is no linking of fuel choice for water heating and cooking as is done for new construction. Technology switching across fuels upon replacement is allowed for space heating, air conditioning, water heating, cooking and clothes drying.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 29
Residential Demand Module Once the fuel and technology choice for a particular end use is determined, the second stage of the choice methodology determines efficiency. In any given year, there are several available prototypes of varying efficiency (minimum standard, some intermediate levels, and highest efficiency). Efficiency choice is based on a functional form and coefficients which give greater or lesser importance to the installed capital cost ("rst cost) versus the operating cost. Generally, within a technology class, the higher the "rst cost, the lower the operating cost. For new construction, efficiency choices are made based on the costs of both the heating and cooling equipment and the building shell characteristics.
The parameters for the second stage efficiency choice are calibrated to the most recently available shipment data for the major residential appliances. Shipment efficiency data are obtained from industry associations which monitor shipments, such as the Association of Home Appliance Manufacturers. Because of this calibration procedure, the model allows the relative importance of "rst cost versus operating cost to vary by general technology and fuel type (e.g. natural gas furnace, electric heat pump, electric central air conditioner, etc.). Once the model is calibrated, it is possible to obtain calculations for the apparent discount rates based on the relative weight given to the operating cost savings versus the weight given to the higher initial cost of more efficient equipment.
Hurdle rates in excess of 30 percent are common in the Residential Demand Module. The prevalence of such high apparent hurdle rates by consumers has led to the notion of the efficiency gap that is, there are many investments that could be made that provide rates of return in excess of residential borrowing rates (10 to 20 percent for example). There are several studies which document instances of apparent high discount rates [2]. Once equipment efficiencies for a technology and fuel are determined, the installed efficiency for its entire stock is calculated.
Appliance Stock submodule The Appliance Stock submodule is an accounting framework which tracks the quantity and average efficiency of equipment by end use, technology, and fuel. It separately tracks equipment requirements for new construction and existing housing units.
For existing units, this module calculates the number of units which survive from previous years, allows certain end uses to further penetrate into the existing housing stock and calculates the total number of units required for replacement and further penetration. Air conditioning and clothes drying are the two major end uses not considered to be fully penetrated.
Table 4.3. Capital cost and performance parameters of selected residential distributed generation technologies Combined Installed Average Efficiency Capital Cost Year of Generating Electrical (Elec. + (2009 $ per Service Technology Type Introduction Capacity (kWDC) Efficiency Thermal kWDC)1 Life (Years)
Solar Photovoltaic 2010 3.5 0.150 N/A $7,183 30 2015 4.0 0.175 N/A $5,346 30 2025 5.0 0.197 N/A $4,284 30 2035 5.0 0.200 N/A $4,048 30 Fuel Cell 2010 10 0.364 0.893 $14,837 20 2015 10 0.429 0.859 $14,837 20 2025 10 0.456 0.842 $14,837 20 2035 10 0.479 0.828 $14,837 20 Wind 2010 2 0.13 N/A $7,802 30 2015 3 0.13 N/A $6,983 30 2025 3 0.13 N/A $6,234 30 2035 4 0.13 N/A $5,903 30 1
The original source documents presented solar photovoltaic costs in 2008 dollars, fuel cell and wind costs in 2010 dollars.
Source: Solar photovoltaic: Photovoltaic (PV) Cost and Performance Characteristics for Residential and Commercial Applications (ICF International, 2010).
Fuel cell: Commercial and Industrial CHP Technology Cost and Performance Data Analysis for EIA (SENTECH Incorporated, 2010). Wind: The Cost and Performance of Distributed Wind Turbines, 2010-35 (ICF International, 2010).
30 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Residential Demand Module Once a piece of equipment enters into the stock, an accounting of its remaining life begins. It is assumed that all appliances survive a minimum number of years, after which a fraction of appliances are removed from the stock. Between the minimum and maximum life expectancy, all appliances retire based on a linear decay function. For example, if an appliance has a minimum life of "ve years and a maximum life of 15 years, one-tenth of the units (one divided by 15 minus "ve) are retired in each of years six through 15. It is further assumed that, when a house is retired from the stock, all of the equipment contained in that house retires as well; i.e., there is no second-hand market for this equipment. The assumptions concerning equipment lives are in Table 4.4.
+- ' ' <666=66 &=" "
Equipment Minimum Life Maximum Life Heat Pumps 7 21 Central Forced-Air Furnaces 10 25 Hydronic Space Heaters 20 30 Room Air Conditioners 8 16 Central Air Conditioners 7 21 Gas Water Heaters 4 14 Electric Water Heaters 5 22 Cooking Stoves 16 21 Clothes Dryers 11 20 Refrigerators 7 26 Freezers 11 31 Source: Lawrence Berkeley National Laboratory. Baseline Data for the Residential Sector and Development of a Residential Forecasting Database, May 1994, and analysis of RECS 2001 data.
Fuel Consumption submodule Energy consumption is calculated by multiplying the vintage equipment stocks by their respective UECs. The UECs include adjustments for the average efficiency of the stock vintages, short-term price elasticity of demand and rebound effects on usage (see discussion below), the size of new construction relative to the existing stock, people per household, shell efficiency and weather effects (space heating and cooling). The various levels of aggregated consumption (consumption by fuel, by service, etc.)
are derived from these detailed equipment-speci"c calculations.
Equipment efficiency The average energy consumption of a particular technology is initially based on estimates derived from RECS 2005. Appliance efficiency is either derived from a long history of shipment data (e.g., the efficiency of conventional air-source heat pumps) or assumed based on engineering information concerning typical installed equipment (e.g., the efficiency of ground-source heat pumps). When the average efficiency is computed from shipment data, shipments going back as far as 20 to 30 years are combined with assumptions concerning equipment lifetimes. This allows for not only an average efficiency to be calculated, but also for equipment to be vintaged and retirements to be projected by vintage and efficiency, as older equipment tends to be lower in efficiency and also tends to be retired before newer, more efficient equipment. Once equipment is retired, the Appliance Stock and Technology Choice Modules determine the efficiency of the replacement equipment. It is often the case that the retired equipment is replaced by substantially more efficient equipment.
As the stock efficiency changes over the simulation interval, energy consumption decreases in inverse proportion to efficiency.
Also, as efficiency increases, the efficiency rebound effect (discussed below) will offset some of the reductions in energy consumption by increased demand for the end-use service. For example, if the stock average for electric heat pumps is now ten percent more efficient than in 2005, then all else constant (weather, real energy prices, shell efficiency, etc.), energy consumption per heat pump would average about only nine percent less.
Adjusting for the size of housing units Information derived from RECS 2005 indicates that new construction (post-1990) is on average roughly 26 percent larger than the existing stock of housing. Estimates for the size of each new home built in the projection period vary by type and region, and are determined by a log-trend projection based on historical data from the Bureau of the Census [3]. For existing structures, it is assumed that about one percent of households that existed in 2005 add about 600 square feet to the heated "oor space in each year of the projection period [4]. The energy consumption for space heating, air conditioning, and lighting is assumed to increase with the square footage of the structure. This results in an increase in the average size of a housing unit from 1,618 to 1,774 square feet from 2005 through 2035.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 31
Residential Demand Module Adjusting for weather and climate Weather in any given year always includes short-term deviations from the expected longer-term average (or climate). Recognition of the effect of weather on space heating and air conditioning is necessary to avoid inadvertently projecting abnormal weather conditions into the future. The residential module adjusts space heating and air conditioning UECs by Census Division using data on heating and cooling degree-days (HDD and CDD). A ten-percent increase in HDD would increase space heating consumption by ten percent over what it would have otherwise been. Over the projection period, the residential module uses a ten-year average for heating and cooling degree-days by Census Division, adjusted to account for projected changes population by State.
Short-term price effect and efficiency rebound It is assumed that energy consumption for a given end-use service is affected by the marginal cost of providing that service. That is, all else equal, a change in the price of a fuel will have an opposite, but less than proportional, effect on fuel consumption. The current value for the short-term elasticity parameter for non-electric fuels is -0.15 [5]. This value implies that for a 1-percent increase in the price of a fuel, there will be a corresponding decrease in energy consumption of -0.15 percent. Changes in equipment efficiency also affect the marginal cost of providing a service. For example, a 10-percent increase in efficiency will reduce the cost of providing the end-use service by 10 percent. Based on the short-term efficiency rebound parameter, the demand for the service will rise by 1.5 percent (-10 percent multiplied by -0.15). Only space heating, cooling, and lighting are assumed to be affected by both elasticities and the efficiency rebound effect. For electricity, the short-term elasticity parameter is set to -0.30 to account for successful deployment of smart grid projects funded under the American Recovery and Reinvestment Act of 2009 (ARRA09).
Shell efficiency The shell integrity of the building envelope is an important determinant of the heating and cooling load for each type of household.
In the NEMS Residential Demand Module, the shell integrity is represented by an index, which changes over time to re"ect improvements in the building shell. The shell integrity index is dimensioned by vintage of house, type of house, fuel type, service (heating and cooling), and Census Division. The age, type, location, and type of heating fuel are important factors in determining the level of shell integrity. Housing units heated with electricity tend to have less air in"ltration rates than homes that use other fuels.
Homes are classi"ed by age as new (post-2005) or existing. Existing homes are represented by the RECS 2005 survey and are assigned a shell index value based on the mix of homes that exist in the base year (2005). The improvement over time in the shell integrity of these homes is a function of two factorsan assumed annual efficiency improvement and improvements made when real fuel prices increase (no price-related adjustment is made when fuel prices fall). For new construction, building shell efficiency is determined by the relative costs and energy bill savings for several levels of heating and cooling equipment, in conjunction with the building shell attributes. The packages represented in NEMS range from homes that meet the International Energy Conservation Code (IECC) [6] to homes that are built with the most efficient shell components. Shell efficiency in new homes increases over time when energy prices rise, or the cost of more efficient equipment falls, all else equal.
Legislation and regulations American Recovery and Reinvestment Act of 2009 (ARRA09)
The ARRA09 legislation passed in February 2009 provides energy efficiency funding for Federal agencies, State Energy Programs, and block grants, as well as a sizable increase in funding for weatherization. To account for the impact of this funding, it is assumed that the total funding is aimed at increasing the efficiency of the existing housing stock. The assumptions regarding the energy savings for heating and cooling are based on evaluations of the impact of weatherization programs over time. Further, it is assumed each house requires a $2,600 investment to achieve the heating and cooling energy savings cited in [7] and that the efficiency measures last approximately 20 years. Assumptions for funding amounts and timing were revised downward and further into the future based on analysis of the weatherization program by the Inspector General of the Department of Energy [8].
The ARRA09 provisions remove the cap on the 30-percent tax credit for ground-source heat pumps, solar PV, solar thermal water heaters, and small wind turbines through 2016. Additionally, the cap for the tax credits for other energy efficiency improvements, such as windows and efficient furnaces, was increased to $1500 through the end of 2010. Several tax credits were extended at reduced credit levels through the end of 2011 as part of the Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act of 2010.
Successful deployment of smart grid projects based on ARRA09 funding could stimulate more rapid investment in smart grid technologies, especially smart meters on buildings and homes, which would make consumers more responsive to electricity price changes. To represent this, the price elasticity of demand for residential electricity was increased for the services that have the ability to alter energy intensity (e.g., lighting).
32 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Residential Demand Module Energy Improvement and Extension Act of 2008 (EIEA 2008)
EIEA 2008 extends and amends many of the tax credits that were made available to residential consumers in EPACT 2005. The tax credits for energy-efficient equipment can now be claimed through 2016, while the $2000 cap for solar technologies has been removed. Additionally, the tax credit for ground-source (geothermal) heat pumps was increased to $2000. The production tax credits for dishwashers, clothes washers, and refrigerators were extended by one to two years, depending on the efficiency level and product. See the EPACT 2005 section below for more details about product coverage.
Energy Independence and Security Act of 2007 (EISA 2007)
EISA 2007 contains several provisions that impact projections of residential energy use. Standards for general service incandescent light bulbs are phased in over 2012-2014, with a more restrictive standard speci"ed in 2020. It is estimated that these standards require 29 percent less watts per bulb in the "rst phase-in, increasing to 67 percent in 2020. EISA also updates the dehumidi"er standard speci"ed in EPACT 2005, resulting in a seven-percent increase in electricity savings relative to the EPACT 2005 requirement. New efficiency standards for external power supplies are set for July 1, 2008, reducing electricity use in both the active and no-load modes. Standards are also set for boilers (September 2012) and dishwashers (January 2010).
Lastly, DOE is instructed to create standards for manufactured housing, requiring compliance to the latest International Energy Conservation Code (IECC) by the end of 2011.
Energy Policy Act of 2005 (EPACT05)
The passage of the EPACT05 in August 2005 provides additional minimum efficiency standards for residential equipment and provides tax credits to producers and purchasers of energy-efficient equipment and builders of energy-efficient homes.
The standards contained in EPACT05 include: 190 watt maximum for torchiere lamps in 2006; dehumidi"er standards for 2007 and 2012; and ceiling fan light kit standards in 2007. For manufactured homes that are 30 percent better than the latest code, a $1000 tax credit can be claimed in 2006 and 2007. Likewise, builders of homes that are 50 percent better than code can claim a $2000 credit over the same period. The builder tax credits and production tax credits are assumed to be passed through to the consumer in the form of lower purchase cost. EPACT05 includes production tax credits for energy-efficient refrigerators, dishwashers, and clothes washers in 2006 and 2007, with dollar amounts varying by type of appliance and level of efficiency met, subject to annual caps. Consumers can claim a 10 percent tax credit in 2006 and 2007 for several types of appliances speci"ed by EPACT05, including: energy-efficient gas, propane, or oil furnaces or boilers, energy-efficient central air conditioners, air and ground source heat pumps, hot water heaters, and windows. Lastly, consumers can claim a 30 percent tax credit in 2006 and 2007 for purchases of solar PV, solar water heaters, and fuel cells, subject to a cap.
Residential alternative cases Technology cases In addition to the AEO2012 Reference case, the Residential Demand Module contributes alternate assumptions to seven integrated side cases developed to examine the effect of different assumptions of technology and policy on energy use. Three cases are devoted to technology assumptions in the demand sectors: the 2011 Technology case, a High Technology case, and a Best Available Technology case. Two cases, the Integrated Low Technology and High Technology cases, combine demand sector technology assumptions with alternative technology assumptions for renewable and fossil fuel electricity generation technologies. Two cases examine policy continuation impacts: the No Sunset case and the Extended Policies case.
The 2011 Technology assumptions specify that all future equipment purchases are made based only on equipment available in 2011. These cases further assume that existing building shell efficiencies will not improve beyond 2011 levels. The 2011 Technology assumptions are implemented in the 2011 Integrated Demand Technology case and the Integrated Low Technology case.
The High Technology assumptions include earlier availability, lower costs, and/or higher efficiencies for more advanced equipment than the Reference case. Equipment assumptions developed by engineering technology experts re"ect the potential impact on technology given increased research and development into more advanced technologies [9]. In the High Technology cases, all new construction is assumed to meet Energy Star speci"cations after 2016. In addition, consumers are assumed to evaluate energy efficiency investments at a discount rate of seven percent real. The High Technology assumptions are implemented in the Integrated High Demand Technology case and the Integrated High Technology case.
The Best Available Technology case assumptions require that all equipment purchases from 2012 forward are based on the highest available efficiency in the High Technology case in a particular modeled year, disregarding the economic costs of such a case. This case is designed to show how much the choice of the highest-efficiency equipment could affect energy consumption.
In this case, all new construction is built to the most efficient speci"cations after 2011. In addition, consumers are assumed to evaluate energy efficiency investments at discount rate of seven percent real.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 33
Residential Demand Module Policy cases The No Sunset case assumes the extension of all existling energy policies and legislation that contain sunset provisions. For the residential sector, this primarily involves tax credits for distributed generation and efficient end-use equipment. The Extended Policy case assumes additional rounds of appliance standards for most end-use equipment while maintaining the No Sunset tax credit assumptions for distributed generation, solar water heaters, and geothermal heat pumps. Standard levels are established based on current Energy Star guidelines. The Extended Policy case also adds multiple rounds of building codes by 2026.
34 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Residential Demand Module Notes and sources
[1] The Model Documentation Report contains additional details concerning model structure and operation. Refer to Energy Information Administration, Model Documentation Report: Residential Sector Demand Module of the National Energy Modeling System, DOE/EIA-M067(2011), (November 2011).
[2] Among the explanations often mentioned for observed high average implicit discount rates are: market failures, (i.e.,
cases where incentives are not properly aligned for markets to result in purchases based on energy economics alone);
unmeasured technology costs (i.e., extra costs of adoption which are not included or difficult to measure, like employee down-time); characteristics of efficient technologies viewed as less desirable than their less-efficient alternatives (such as equipment noise levels or lighting quality characteristics); and the risk inherent in making irreversible investment decisions. Examples of market failures/barriers include: decision-makers having less than complete information, cases where energy equipment decisions are made by parties not responsible for energy bills (e.g., landlord/tenants, builders/
home buyers), discount horizons which are truncated (which might be caused by mean occupancy times that are less than the simple payback time and that could possibly be classi"ed as an information failure), and lack of appropriate credit vehicles for making efficiency investments. The use of high implicit discount rates in NEMS merely recognizes that such rates are typically found to apply to energy-efficiency investments.
[3] U.S. Bureau of Census, Series C25 Data from various years of publications.
[4] Sources: U.S. Bureau of Census, Annual Housing Survey 2001 and Professional Remodeler, 2002 Home Remodeling Study.
[5] See Dahl, Carol, A Survey of Energy Demand Elasticities in Support of the Development of the NEMS, October 1993.
[6] The IECC established guidelines for builders to meet speci"c targets concerning energy efficiency with respect to heating and cooling load.
[7] Oak Ridge National Laboratory, Estimating the National Effects of the U.S. Department of Energys Weatherization Assistance Program with State-Level Data: A Metaevaluation Using Studies from 1993 to 2005, September 2005.
[8] U.S. Department of Energy, Office of Inspector General, Office of Audit Services, Special Report: Progress in Implementing the Department of Energys Weatherization Assistance Program under the American Recovery and Reinvestment Act, February 2010.
[9] The high technology assumptions are based on Energy Information Administration, (Technology Forecast Updates-Residential and Commercial Building Technologies-Advanced Adoption Case) (Navigant Consulting, September 2011).
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 35
THIS PAGE INTENTIONALLY LEFT BLANK Commercial Demand Module THIS PAGE INTENTIONALLY LEFT BLANK Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The de"nition of the commercial sector is consistent with EIAs State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.
Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].
The commercial module projects consumption by fuel [2] at the Census division level using prices from the NEMS energy supply modules and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are projected for ten end-use services [3] for eleven building categories [4] in each of the nine Census divisions (see Figure 5). The model begins by developing projections of "oorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected "oorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then chosen to meet the projected service demands for the seven major end uses [5]. Once technologies are chosen, the energy consumed by the equipment stock (both existing and purchased equipment) is developed to meet the projected end-use service demands [6].
Key assumptions The key assumptions made by the commercial module are presented in terms of the "ow of the calculations described above.
The sections below summarize the assumptions in each of the commercial module submodules: "oorspace, service demand, distributed generation, technology choice, and end-use consumption. The submodules are executed sequentially in the order presented, and the outputs of each submodule become the inputs to subsequently executed submodules. As a result, key projection drivers for the "oorspace submodule are also key drivers for the service demand submodule, and so on.
Floorspace submodule Floorspace is projected by starting with the previous years stock of "oorspace and eliminating a portion to represent the age-related removal of buildings. Total "oorspace is the sum of the surviving "oorspace plus new additions to the stock derived from the MAM "oorspace growth projection [7].
Existing "oorspace and attrition Existing "oorspace is based on the estimated "oorspace reported in the 2003 Commercial Buildings Energy Consumption Survey (Table 5.1). Over time, the 2003 stock is projected to decline as buildings are removed from service ("oorspace attrition). Floorspace attrition is estimated by a logistic decay function, the shape of which is dependent upon the values of two parameters: average building lifetime and gamma. The average building lifetime refers to the median expected lifetime of a particular building type. The gamma parameter corresponds to the rate at which buildings retire near their median expected lifetime. The current values for the average building lifetime and gamma vary by building type as presented in Table 5.2 [8].
New construction additions to "oorspace The commercial module develops estimates of projected commercial "oorspace additions by combining the surviving "oorspace estimates with the total "oorspace projection from MAM. A total NEMS "oorspace projection is calculated by applying the MAM assumed "oorspace growth rate within each Census division and MAM building type to the corresponding NEMS Commercial Demand Modules building types based on the CBECS building type shares. The NEMS surviving "oorspace from the previous year is then subtracted from the total NEMS "oorspace projection for the current year to yield new "oorspace additions [9].
Service demand submodule Once the building stock is projected, the Commercial Demand module develops a projection of demand for energy-consuming services required for the projected "oorspace. The module projects service demands for the following explicit end-use services:
space heating, space cooling, ventilation, water heating, lighting, cooking, refrigeration, personal computer office equipment, and other office equipment [10]. The service demand intensity (SDI) is measured in thousand Btu of end-use service demand per square foot and differs across service, Census division, and building type. The SDIs are based on a hybrid engineering and statistical approach of CBECS consumption data [11]. Projected service demand is the product of square feet and SDI for all end uses across the eleven building categories with adjustments for changes in shell efficiency for space heating and cooling.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 39
Commercial Demand Module
+- + " > -4!? - ""4
million of square feet Food Food Health Large Small Merc/
Assembly Education Sales Service Care Lodging Office Office Service Warehouse Other Total New England 431 299 75 45 48 374 282 320 819 411 351 3,452 Middle Atlantic 1,243 1,384 163 127 310 797 1,523 1,065 1,641 1,112 1,177 10,543 East North Central 1,355 1,990 218 248 316 549 1,297 1,129 2,148 2,023 1,152 12,424 West North Central 772 552 102 206 123 595 219 704 1,045 994 369 5,580 South Atlantic 1,161 2,445 223 433 469 939 1,173 1,065 3,391 1,836 865 13,999 East South Central 546 341 67 99 134 368 195 371 985 390 223 3,719 West South Central 965 1,198 197 232 235 387 916 501 2,076 1,740 575 9,022 Mountain 411 640 64 32 94 438 230 535 1,087 506 168 4,207 Paci"c 809 1,027 146 232 176 649 1,028 915 2,051 1,066 515 8,613 Total United States 7,693 9,874 1,255 1,654 1,905 5,096 6,861 6,605 15,242 10,078 5,395 71,658 Note: Totals may not equal sum of components due to independent rounding.
Source: U.S. Energy Information Administration, 2003 Commercial Buildings Energy Consumption Survey Public Use Data.
Table 5.2. Floorspace attrition parameters Food Food Health Large Small Merc/
Assembly Education Sales Service Care Lodging Office Office Service Warehouse Other Median Expected Lifetime (years) 55 62 55 50 55 53 65 58 50 58 60 Gamma 2.2 2.1 2.3 2.0 2.5 2.1 2.0 2.0 2.2 2.0 2.3 Source: U.S. Energy Information Administration, Commercial Buildings Energy Consumption Survey 2003, 1999, 1995, 1992, and 1989 Public Use Data, 1986 Nonresidential Buildings Energy Consumption Survey, McGraw-Hill Construction Dodge Annual Starts - non-residential building starts, Northwest Energy Efficiency Alliance, Assessment of the Commercial Building Stock in the Paci"c Northwest, KEMA-XENERGY, Inc., March 2004, and public information on demolitions.
Shell efficiency The shell integrity of the building envelope is an important determinant of the heating and cooling loads for each type of building.
In the NEMS Commercial Demand Module, the shell efficiency is represented by separate building shell heating and cooling factors which change over time to re"ect improvements in the building shell. The factors, dimensioned by building type and Census division, affect the space heating and cooling service demand intensities causing changes in fuel consumed for these services as the shell integrity improves. In the AEO2012 Reference case building shells for new construction built in 2003 are up to 49 percent more efficient with respect to heating and up to 30 percent more efficient with respect to cooling relative to the average shell for existing buildings of the same type. Over the projection horizon, new building shells improve in efficiency by 14 percent relative to their efficiency in 2003. For existing buildings, efficiency is assumed to increase by 6 percent over the 2003 stock average.
Distributed generation and combined heat and power Program-driven installations of solar photovoltaic systems are based primarily on information from the Interstate Renewable Energy Councils annual report on U.S. solar market trends. Historical data from Form EIA-860, Annual Electric Generator Report, are used to derive electricity generation for 2004 through 2009 by Census division, building type and fuel. A projection of distributed generation and combined heat and power (CHP) of electricity is developed based on the economic returns projected for distributed generation and CHP technologies. The model uses a detailed cash-"ow approach to estimate the internal rate of return for an investment. Penetration assumptions for distributed generation and CHP technologies are a function of the estimated internal rate of return relative to purchased electricity. Table 5.3 provides the cost and performance parameters for representative distributed generation and CHP technologies.
40 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Commercial Demand Module The model also incorporates endogenous learning for new distributed generation and CHP technologies, allowing for declining technology costs as shipments increase. For fuel cell and photovoltaic systems, parameter assumptions for the AEO2012 Reference case result in a 13-percent reduction in capital costs each time the number of units shipped to the buildings sectors (residential and commercial) doubles. Doubling the number of microturbines shipped results in a 10-percent reduction in capital costs and doubling the number of distributed wind systems shipped results in a 3-percent reduction.
Technology Choice Submodule The technology choice submodule develops projections of the results of the capital purchase decisions for equipment fueled by the three major fuels (electricity, natural gas, and distillate fuel). Capital purchase decisions are driven by assumptions concerning behavioral rule proportions and time preferences, described below, as well as projected fuel prices, average utilization of equipment (the capacity factors), relative technology capital costs, and operating and maintenance (O&M) costs.
Decision types In each projection year, equipment is potentially purchased for three decision types. Equipment must be purchased for newly added "oorspace and to replace the portion of equipment in existing "oorspace that is projected to wear out [12]. Equipment is also potentially purchased for retro"tting equipment that has become economically obsolete. The purchase of retro"t equipment occurs only if the annual operating costs of a current technology exceed the annualized capital and operating costs of a technology available as a retro"t candidate.
Behavioral rules The commercial module allows the use of three alternate assumptions about equipment choice behavior. These assumptions constrain the equipment selections to three choice sets, which are progressively more restrictive. The choice sets vary by decision type and building type:
t Unrestricted Choice Behavior - This rule assumes that commercial consumers consider all types of equipment that meet a given service, across all fuels, when faced with a capital purchase decision.
t Same Fuel Behavior - This rule restricts the capital purchase decision to the set of technologies that consume the same fuel that currently meets the decision makers service demand.
t Same Technology Behavior - Under this rule, commercial consumers consider only the available models of the same technology and fuel that currently meet service demand, when facing a capital stock decision.
Under any of the above three behavior rules, equipment that meets the service at the lowest annualized lifecycle cost is chosen.
Table 5.4 illustrates the proportions of "oorspace subject to the different behavior rules for space heating technology choices in large office buildings.
Time preferences Commercial building owners time preferences regarding current versus future expenditures are assumed to be distributed among seven alternate time preference premiums. Adding the risk-adjusted time preference premiums to the 10-year Treasury note rate from MAM results in implicit discount rates, also known as hurdle rates, applicable to the assumed proportions of commercial "oorspace. The effect of the use of this distribution of discount rates is to prevent a single technology from dominating purchase decisions in the lifecycle cost comparisons. The distribution used for AEO2012 assigns some "oorspace a very high discount or hurdle rate to simulate "oorspace which will never retro"t existing equipment and which will only purchase equipment with the lowest capital cost. Discount rates for the remaining six segments of the distribution get progressively lower, simulating increased sensitivity to the fuel costs of the equipment that is purchased. The share of "oorspace assigned to each rate in the distribution varies by end-use service. Table 5.5 illustrates the distribution of time preference premiums for space heating and lighting in 2015. The proportion of "oorspace assumed for the 0.0 time preference premium represents an estimate of the Federally-owned commercial "oorspace that is subject to purchase decisions in a given year. The Federal sector is expected to purchase energy-efficient equipment to meet the Federal buildings performance standards of the Energy Policy Act of 2005 and the Energy Independence and Security Act of 2007 whenever cost-effective. For Federal purchase decisions relating to energy conservation, cost-effectiveness is determined using a discount rate based on long-term Treasury bond rates, approximated in the commercial module by the 10-year Treasury note rate. For lighting, the proportion of "oorspace assumed for the 0.0 time preference premium is increased to include all Federal "oorspace starting in 2009 to represent the EISA 2007 provision that all Federal buildings be equipped with energy-efficient lighting "xtures and bulbs to the maximum extent feasible, including when replacing bulbs in existing "xtures.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 41
Commercial Demand Module
+- !" "& 66" & " 66 "-"" "$
Average Combined Installed Generating Efficiency Capital Cost Service Year of Capacity Electrical (Elec. + (2009 $ per Life Technology Type Introduction (kWDC) Efficiency Thermal) kWDC)* (Years)
Solar Photovoltaic 2010 32 0.15 N/A $6,874 30 2015 35 0.18 N/A $5,109 30 2025 40 0.20 N/A $4,067 30 2035 45 0.20 N/A $3,837 30 Fuel Cell 2010 200 0.42 0.65 $7,199 20 2015 200 0.48 0.66 $5,019 20 2025 200 0.51 0.69 $4,016 20 2035 200 0.54 0.73 $3,180 20 Natural Gas Engine 2010 334 0.30 0.82 $1,780 20 2015 334 0.31 0.85 $1,630 20 2025 334 0.30 0.87 $1,251 20 2035 334 0.30 0.91 $831 20 Oil-"red Engine 2010 300 0.34 0.73 $1,784 20 2015 300 0.34 0.74 $1,746 20 2025 300 0.35 0.80 $1,669 20 2035 300 0.36 0.78 $1,592 20 Natural Gas Turbine 2010 3510 0.25 0.76 $1,890 20 2015 3510 0.25 0.77 $1,858 20 2025 3510 0.25 0.80 $1,760 20 2035 3510 0.25 0.82 $1,645 20 Natural Gas Microturbine 2010 200 0.32 0.61 $2,414 20 2015 200 0.34 0.67 $2,098 20 2025 200 0.37 0.73 $1,467 20 2035 200 0.40 0.80 $836 20 Wind 2010 32 0.13 N/A $5,224 30 2015 35 0.13 N/A $4,715 30 2025 40 0.13 N/A $3,973 30 2035 50 0.13 N/A $3,627 30
- The original source documents presented solar photovoltaic costs in 2008 dollars, all other technologies in 2010 dollars. Costs for solar photovoltaic, fuel cell, microturbine, and wind technologies include learning effects.
Sources: U.S. Energy Information Administration, Commercial and Industrial CHP Technology Cost and Performance Data Analysis for EIA SENTECH, Inc.,
and SAIC, Inc., June 2010, U.S. Energy Information Administration, Photovoltaic (PV) Cost and Performance Characteristics for Residential and Commercial Applications Final Report, ICF International, August 2010, and U.S. Energy Information Administration, The Cost and Performance of Distributed Wind Turbines, 2010-35 Final Report, ICF International, August 2010.
42 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Commercial Demand Module
+- ' 56-$ & $ $"#6" &-
percent Unrestricted Same Fuel Same Technology Total New Equipment Decision 21 30 49 100 Replacement Decision 7 31 62 100 Retro"t Decision 1 4 95 100 Source: U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA-M066(2012) (August 2012).
+- 56"-" &@B""6&66& $" $"#6"
2015 percent Time Preference Premium Proportion of Floorspace-Space Heating (2015) Proportion of Floorspace-Lighting (2015) 1000.0 27.0 27.0 100.0 23.0 23.0 45.0 19.0 18.6 25.0 18.6 18.6 15.0 10.7 8.8 6.5 1.5 1.5 0.0 0.2 2.5
-- 100.0 100.0 Source: U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA-M066(2012) (August 2012).
The distribution of hurdle rates used in the commercial module is also affected by changes in fuel prices. If a fuels price rises relative to its price in the base year (2003), the non"nancial portion of each hurdle rate in the distribution decreases to re"ect an increase in the relative importance of fuel costs, expected in an environment of rising prices. Parameter assumptions for AEO2012 result in a 30-percent reduction in the non"nancial portion of a hurdle rate if the fuel price doubles. If the risk-adjusted time preference premium input by the model user results in a hurdle rate below the assumed "nancial discount rate for the commercial sector, 15 percent, with base year fuel prices (such as the 0.0 rate given in Table 5.5), no response to increasing fuel prices is assumed.
Technology characterization database The technology characterization database organizes all relevant technology data by end use, fuel, and Census division.
Equipment is identi"ed in the database by a technology index as well as a vintage index, the index of the fuel it consumes, the index of the service it provides, its initial market share, the Census division index for which the entry under consideration applies, its efficiency (or coefficient of performance or efficacy in the case of lighting equipment), installed capital cost per unit of service demand satis"ed, operating and maintenance cost per unit of service demand satis"ed, average service life, year of initial availability, and last year available for purchase. Equipment may only be selected to satisfy service demand if the year in which the decision is made falls within the window of availability. Equipment acquired prior to the lapse of its availability continues to be treated as part of the existing stock and is subject to replacement or retro"tting. This "exibility in limiting equipment availability allows the direct modeling of equipment efficiency standards. Table 5.6 provides a sample of the technology data for space heating in the New England Census division.
An option has been included to allow endogenous price-induced technological change in the determination of equipment costs and availability for the menu of equipment. This concept allows future technologies faster diffusion into the market place if fuel prices increase markedly for a sustained period of time. The option was not exercised for the AEO2012 model runs.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 43
Commercial Demand Module End-Use Consumption Submodule The end-use consumption submodule calculates the consumption of each of the three major fuels (electricity, natural gas, and distillate fuel oil) for the ten end-use services plus fuel consumption for combined heat and power and district services. For the ten end-use services, energy consumption is calculated as the end-use service demand met by a particular type of equipment divided by its efficiency and summed over all existing equipment types. This calculation includes dimensions for Census division, building type, and fuel. Consumption of the "ve minor fuels (residual fuel oil, lique"ed petroleum gas, motor gasoline, kerosene, and coal) is projected based on historical trends.
Equipment efficiency The average energy consumption of a particular appliance is based initially on estimates derived from the 2003 CBECS. As the stock efficiency changes over the model simulation, energy consumption decreases nearly as much as, but not quite proportionally to the efficiency increase. The difference is due to the calculation of efficiency using the harmonic average and also the efficiency rebound effect discussed below. For example, if on average, electric heat pumps are now 10 percent more efficient than in 2003, then all else constant (weather, real energy prices, shell efficiency, etc.), energy consumption per heat pump would now average about 9 percent less. The Service Demand and Technology Choice Submodules together determine the average efficiency of the stocks used in adjusting the initial average energy consumption.
Adjusting for weather and climate Weather in any given year always includes short-term deviations from the expected longer-term average (or climate).
Recognition of the effect of weather on space heating and air conditioning is necessary to avoid projecting abnormal weather conditions into the future. In the commercial module, proportionate adjustments are made to space heating and air conditioning demand by Census division. These adjustments are based on National Oceanic and Atmospheric Administration (NOAA) data for Heating Degree-Days (HDD) and Cooling Degree-Days (CDD). A 10-percent increase in HDD would increase space heating consumption by 10 percent over what it would have been otherwise. The commercial module uses a 10-year average for HDD and CDD by Census division, adjusted over the projection period by projections for State population shifts.
Short-term price effect and efficiency rebound It is assumed that energy consumption for a given end-use service is affected by the marginal cost of providing that service. That is, all else equal, a change in the price of a fuel will have an inverse, but less than proportional, effect on fuel consumption. The current value for the short-term price elasticity parameter is -0.25 for all major end uses except refrigeration. A value of -0.1 is currently used for commercial refrigeration. A value of -0.05 is currently used for PC and non-PC office equipment and other minor uses of electricity. For example, for lighting, this value implies that for a 1 percent increase in the price of a fuel, there will be a corresponding decrease in energy consumption of 0.25 percent. Another way of affecting the marginal cost of providing a service is through equipment efficiency. As equipment efficiency changes over time, so will the marginal cost of providing the end-use service. For example, a 10-percent increase in efficiency will reduce the cost of providing the service by 10 percent.
The short-term elasticity parameter for efficiency rebound effects is -0.15 for affected end uses; therefore, the demand for the service will rise by 1.5 percent (-10 percent x -0.15). Currently, all services are affected by the short-term price effect and services affected by efficiency rebound are space heating and cooling, water heating, ventilation and lighting.
J " "
American Recovery and Reinvestment Act of 2009 (ARRA09)
The ARRA09 legislation passed in February 2009 provides energy efficiency funding for Federal agencies, State Energy Programs, and block grants. To account for the impact of this funding, States are assumed to adopt and enforce the ASHRAE 90.1-2007 standard by 2018 for building shell measures, and all Public buildings (Federal, state, and local) are assumed to use the 10-year Treasury note rate for purchase decisions related to both new construction and replacement equipment while stimulus funding is available. A percentage of the State Energy Program and Conservation Block Grant funding is assumed to be used for solar photovoltaic and small wind turbine installations. Additional stimulus funding is applied to fuel cell installations.
The ARRA09 provisions remove the cap on the 30-percent Business Investment Tax Credit for wind turbines. The Investment Tax Credit is still available for systems installed through 2016. These credits are directly incorporated into the cash-"ow approach for distributed generation systems.
Energy Improvement and Extension Act of 2008 (EIEA08)
The EIEA08 legislation passed in October 2008 extends the Business Investment Tax Credit provisions of the Energy Policy Act of 2005 and expands the credit to include additional technologies. The Business Investment Tax Credits of 30 percent for solar energy systems and fuel cells and 10 percent for microturbines are extended through 2016. The cap on the fuel cell credit has been increased from $500 to $1,500 per half kilowatt of capacity. The EIEA08 provisions expand the Investment Tax Credit to 44 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Commercial Demand Module
+- P !" "&4" & " 66 $"#6"1 Capital Cost Maintenance Cost (2010$ per Mbtu/ (2007$ per Mbtu/ Service Life Equipment Type Vintage Efficiency2 hour)3 hour)3 (Years)
Electric Rooftop Heat Pump 2003 - installed base 3.10 $63.89 $1.39 15 2010 - current standard/typical 3.30 $76.67 $1.39 15 2010 - installed base 3.40 $96.67 1.39 15 Ground-source Heat Pump 2003 - typical 3.40 $140.00 $16.80 20 2010 - high 3.50 $140.00 $16.80 20 2010 - typical 4.90 $170.00 $16.80 20 Electric Boiler 2003 installed base 0.94 $15.64 $0.24 15 Packaged Electric Current typical 0.98 $21.76 $0.01 18 Natural Gas Heat Pump 2003 installed base - absorption 1.30 $158.33 $2.50 15 2010 - typical - engine-driven 1.40 $312.50 $4.58 30 2020 - typical - engine-driven 1.40 $212.50 $4.58 30 2030 - typical - engine-driven 1.40 $129.17 $4.58 30 Natural Gas Furnace 2003 installed base 0.71 $9.85 $1.06 17.5 2010 current standard/typical 0.78 $9.84 $0.97 17.5 2010 high 0.80 $10.30 $0.94 17.5 2020 high 0.88 $10.67 $0.86 17.5 2030 high 0.89 $11.48 $0.85 17.5 2035 high 0.91 $12.25 $0.83 17.5 Natural Gas Boiler 2003 installed base 0.73 $20.55 $0.77 25 2010 current standard/typical 0.78 $25.64 $0.72 25 2012 standard 0.80 $21.02 $0.47 25 2012 mid range 0.89 $28.79 $0.63 25 2010 high 0.97 $38.02 $0.58 25 2030 typical 0.80 $32.03 $0.70 25 Distillate Oil furnace 2003 installed base 0.76 $13.56 $0.99 18.5 2010 typical 0.80 $13.28 $0.94 18.5 2020 typical 0.80 $13.28 $0.94 18.5 Distillate Oil Boiler 2003 installed base 0.76 $17.54 $0.17 25 2010 current standard 0.81 $18.21 $0.16 25 2012 standard 0.82 $18.10 $0.16 25 2010 high 0.87 $25.05 $0.13 25 2020 typical 0.82 $18.10 $0.16 25 2020 high 0.87 $25.05 $0.13 25 Equipment listed is for the New England Census division, but is also representative of the technology data for the rest of the U.S. See the source reference below for the complete set of technology data.
2 Efficiency measurements vary by equipment type. Electric rooftop air-source heat pumps, ground source and natural gas heat pumps are rated for heating performance using coefficient of performance; natural gas and distillate furnaces and boilers are based on Thermal Efficiency.
3 Capital and maintenance costs are given in 2007 dollars.
Source: U.S. Energy Information Administration, EIA - Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case, Navigant Consulting, Inc., October 2011.
include a 10-percent credit for CHP systems and ground-source heat pumps and a 30-percent credit for wind turbines with the wind credit capped at $4,000. The expanded credits are available for systems installed through 2016. These credits are directly incorporated into the cash-"ow approach for distributed generation systems, including CHP, and factored into the installed capital cost assumptions for solar hot water heaters and ground-source heat pumps.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 45
Commercial Demand Module Energy Independence and Security Act of 2007 (EISA07)
The EISA07 legislation passed in December 2007 provides standards for speci"c explicitly modeled commercial equipment. The EISA07 requires speci"c energy-efficiency measures in commercial walk-in coolers and walk-in freezers effective January 1, 2009.
Incandescent and halogen lamps must meet standards for maximum allowable wattage based on lumen output starting in 2012 and metal halide lamp "xtures using lamps between 150 and 500 watts are required to have a minimum ballast efficiency ranging from 88 to 94 percent, depending on ballast type, effective January 1, 2009.
The EISA07 requirement for Federal buildings to use energy-efficient lighting "xtures and bulbs to the maximum extent possible is represented by adjusting the proportion of the commercial sector assumed to use the 10-year Treasury note rate as an implicit discount or hurdle rate for lighting.
Energy Policy Act of 2005 (EPACT05)
The passage of the EPACT05 in August 2005 provides additional minimum efficiency standards for commercial equipment. Some of the standards for explicitly modeled equipment, effective January 1, 2010, include: an Energy Efficiency Rating (EER) ranging from 10.8 to 11.2 for small package air conditioning and heating equipment; daily electricity consumption limits by volume for commercial refrigerators, freezers, and refrigerator-freezers; and electricity consumption limits per 100 pounds of ice produced based on equipment type and capacity for automatic ice makers. The EPACT05 adds standards for medium base compact "uorescent lamps effective January 1, 2006, for ballasts for Energy Saver "uorescent lamps effective in 2009 and 2010, and bans the manufacture or import of mercury vapor lamp ballasts effective January 1, 2008.
Several efficiency standards in the EPACT05 pertain to equipment not explicitly represented in the NEMS Commercial Demand Module. For low voltage dry-type transformers, effects of the standard are included in estimating the share of projected miscellaneous electricity use attributable to transformer losses. For illuminated exit signs, traffic signals, and commercial premise spray valves, assumed energy reductions are calculated based on per-unit savings relative to a baseline unit and the estimated share of installed units and sales that already meet the standard. Total projected reductions are phased in over time to account for stock turnover. Under the EPACT05 standards, illuminated exit signs and traffic signal modules must meet ENERGY STAR program requirements as of January 1, 2006. The requirements limit input power demand to 5 watts or less per face for exit signs. Nominal wattages for traffic signal modules are limited to 8 to 15 watts, based on module type. Effective January 1, 2007, low voltage dry-type distribution transformers are required to meet the National Electrical Manufacturers Association Class I Efficiency Levels with minimum efficiency levels ranging from 97 percent to 98.9 percent based on output. Commercial pre-rinse spray valves [13] must have a maximum "ow rate of 1.6 gallons per minute, effective January 1, 2006 with energy reductions attributed to hot water use.
The EPACT05 expands the Business Investment Tax Credit to 30 percent for solar property installed in 2006 and 2007. Business Investment Tax Credits of 30 percent for fuel cells and 10 percent for microturbine power plants are also available for property installed in 2006 and 2007. The EPACT05 tax credit provisions were extended in December 2006 to cover equipment installed in 2008. These credits are directly incorporated into the cash-"ow approach for distributed generation systems and factored into the installed capital cost assumptions for solar hot water heaters.
Energy Policy Act of 1992 (EPACT92)
A key assumption incorporated in the technology selection process is that the equipment efficiency standards described in the EPACT92 constrain minimum equipment efficiencies. The effects of standards are modeled by modifying the technology database to eliminate equipment that no longer meets minimum efficiency requirements. Some of the EPACT92 standards implemented in the module include: gas and oil-"red boilersminimum combustion efficiency of 0.80 and 0.83, respectively, amended to minimum thermal efficiency of 0.80 and 0.81, respectively, in 2012; gas and oil-"red furnacesminimum thermal efficiency of 0.80 and 0.81, respectively; electric water heatersminimum energy factor of 0.85; and gas and oil water heatersminimum thermal efficiency of 0.80 and 0.78, respectively. A "uorescent lamp ballast standard effective in 2005 mandates electronic ballasts with a minimum ballast efficacy factor of 1.17 for 4-foot, 2-lamp ballasts and 0.63 for 8-foot, 2-lamp ballasts. Fluorescent lamps and incandescent re"ector lamb bulbs must meet amended standard levels for minimum average lamp efficacy in 2012.
Recent updates for commercial refrigeration equipment include maximum energy consumption standards for refrigerated vending machines and display cases based on volume.
The 10-percent Business Investment Tax Credit for solar energy property included in EPACT92 is directly incorporated into the cash-"ow approach for projecting distributed generation by commercial photovoltaic systems. For solar hot water heaters, the tax credit is factored into the installed capital cost assumptions used in the technology choice submodule.
46 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Commercial Demand Module Energy efficiency programs Several energy efficiency programs affect the commercial sector. These programs are designed to stimulate investment in more efficient building shells and equipment for heating, cooling, lighting, and other end uses. The commercial module includes several features that allow projected efficiency to increase in response to voluntary programs (e.g., the distribution of risk-adjusted time preference premiums and shell efficiency parameters). Retro"ts of equipment for space heating, air conditioning and lighting are incorporated in the distribution of premiums given in Table 5.5. Also the shell efficiency of new and existing buildings is assumed to increase from 2003 through 2035. Shells for new buildings increase in efficiency by 14 percent over this period, while shells for existing buildings increase in efficiency by 6 percent.
! 66 ""
Technology cases In addition to the AEO2012 Reference case, three side cases were developed to examine the effect of equipment and building standards on commercial energy usea 2011 Technology case, a High Technology case, and a Best Available Technology case.
These side cases were analyzed in stand-alone (not integrated with the NEMS demand and supply modules) buildings (residential and commercial) modules runs and thus do not include supply responses to the altered commercial consumption patterns of the three cases. AEO2012 also analyzed an Integrated High Technology case, which combines the High Technology cases of the four end-use demand sectors, the Electricity Low Fossil Technology Cost case, the Low Nuclear Cost case, and the Low Renewable Cost case, and an Integrated 2011 Technology case, which combines the 2011 Technology cases of the end-use demand sectors, the Electricity High Fossil Technology Cost case, the High Nuclear Cost case, and the High Renewable Cost case.
The 2011 Technology case assumes that all future equipment purchases are made based only on equipment available in 2011. This case assumes building shell efficiency to be "xed at 2011 levels. In the High Technology case, depending on technology or end use, equipment costs are lower, efficiencies are higher, and equipment is available sooner than in the Reference case. Energy efficiency investments are evaluated at 7 percent real rather than the distribution of hurdle rates assumed for the Reference case. Equipment assumptions were developed by engineering technology experts, considering the potential impact on technology given increased research and development into more advanced technologies. In the High Technology case, building shell efficiencies are assumed to improve 25 percent more than in the Reference case after 2011. Existing building shells, therefore, increase by 7.5 percent relative to 2003 levels and new building shells by 17.4 percent relative to their efficiency in 2003 by 2035.
The Best Available Technology case assumes that all equipment purchases after 2010 are based on the highest available efficiency for each type of technology in the High Technology case in a particular simulation year, disregarding the economic costs of such a case. It is designed to show how much the choice of the highest-efficiency equipment could affect energy consumption. Shell efficiencies in this case are assumed to improve 50 percent more than in the Reference case after 2011, i.e., existing shells increase by 9 percent relative to 2003 levels and new building shells by 20.8 percent relative to their efficiency in 2003 by 2035.
Fuel shares, where appropriate for a given end use, are allowed to change in the technology cases as the available technologies from each technology type compete to serve certain segments of the commercial "oorspace market. For example, in the Best Available Technology case, the most efficient gas furnace technology competes with the most efficient electric heat pump technology. This contrasts with the Reference case, in which a greater number of technologies for each fuel with varying efficiencies all compete to serve the heating end use. In general, the fuel choice will be affected as the available choices are constrained or expanded, and will thus differ across the cases.
Two sensitivities that focus on electricity generation incorporate alternative assumptions for non-hydro renewable energy technologies in the power sector, the industrial sector, and the buildings sectors, including residential and commercial photovoltaic and wind systems. In each of these cases, assumptions regarding non-renewable technologies are not changed from the Reference case.
The High Renewable Cost case assumes that the cost and performance characteristics for residential and commercial photovoltaic and wind systems remain "xed at 2011 levels through the projection horizon. The Low Renewable Cost case assumes that costs for residential and commercial photovoltaic and wind systems are 20 percent below Reference case assumptions in 2012, declining to at least 40 percent lower than Reference case cost estimates by 2035.
Analysis cases Two integrated analysis cases were completed for the AEO2012: the No Sunset and Extended Policies cases. Both cases are based upon Reference case assumptions, with additional changes made to extend existing tax credits and policies beyond those prescribed by current law.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 47
Commercial Demand Module In the No Sunset case, the 30-percent solar photovoltaic investment tax credit (ITC) that is scheduled to revert to a 10-percent credit in 2016 is, instead, assumed to be extended inde"nitely at 30 percent. Additional tax credits for the purchase of other energy-efficient equipment, such as ground-source heat pumps, are also assumed to be extended inde"nitely as opposed to expiring in 2016.
The Extended Policies case adopts the same assumptions as the No Sunset case and includes additional changes. For instance, Federal equipment efficiency standards are updated at particular intervals consistent with the provisions in the existing law, with the levels based on ENERGY STAR speci"cations, or Federal Energy Management Program (FEMP) purchasing guidelines for Federal agencies. Standards are also introduced for products that currently are not subject to Federal efficiency standards. Updated national building energy codes reach 30-percent improvement in 2020 relative to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Building Energy Code 90.1-2004 in the commercial sector. Two subsequent rounds in 2023 and 2026 each add an assumed 5-percent incremental improvement to building energy codes.
The equipment standards and building codes assumed for the Extended Policies case are meant to illustrate the potential effects of these polices on energy consumption for buildings. No cost-bene"t analysis or evaluation of impacts on consumer welfare was completed in developing the assumptions. Likewise, no technical feasibility analysis was conducted, although standards were not allowed to exceed maximum technologically feasible levels described in DOEs technical support documents.
48 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Commercial Demand Module Notes and sources
[1] U.S. Energy Information Administration, 2003 Commercial Buildings Energy Consumption Survey (CBECS) Public Use Files, web site www.eia.gov/emeu/cbecs/cbecs2003/public_use_2003/cbecs_pudata2003.html.
[2] The fuels accounted for by the commercial module are electricity, natural gas, distillate fuel oil, residual fuel oil, lique"ed petroleum gas (LPG), coal, motor gasoline, and kerosene. Current commercial use of biomass (wood, Municipal solid waste) is also included. In addition to these fuels the use of solar energy is projected based on an exogenous estimate of existing solar photovoltaic system installations, projected installations due to State and local incentive programs, and the potential endogenous penetration of solar photovoltaic systems and solar thermal water heaters. The use of wind energy is projected based on an estimate of existing distributed wind turbines and the potential endogenous penetration of wind turbines in the commercial sector.
[3] The end-use services in the commercial module are heating, cooling, water heating, ventilation, cooking, lighting, refrigeration, PC and non-PC office equipment and a category denoted other to account for all other minor end uses.
[4] The 11 building categories are assembly, education, food sales, food services, health care, lodging, large offices, small offices, mercantile/services, warehouse and other.
[5] Minor end uses are modeled based on penetration rates and efficiency trends.
[6] The detailed documentation of the commercial module contains additional details concerning model structure and operation. Refer to U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA M066(2012), (August 2012).
[7] The commercial "oorspace equations of the Macroeconomic Activity Model are estimated using the McGraw-Hill Construction Research & Analytics database of historical "oorspace estimates. The McGraw-Hill Construction estimate for commercial "oorspace in the U.S. is approximately 16 percent lower than the estimate obtained from the CBECS used for the Commercial module. See F.W. Dodge, Building Stock Database Methodology and 1991 Results, Construction Statistics and Forecasts, F.W. Dodge, McGraw-Hill.
[8] The commercial module performs attrition for 9 vintages of "oorspace developed using stock estimates from the previous 5 CBECS and historical "oorspace additions data from McGraw-Hill Construction data.
[9] In the event that the computation of additions produces a negative value for a speci"c building type, it is assumed to be zero.
[10] Other office equipment includes copiers, fax machines, typewriters, cash registers, server computers, and other miscellaneous office equipment. A tenth category denoted other includes equipment such as elevators, escalators, medical, and other laboratory equipment, laundry, communications equipment, security equipment, transformers and miscellaneous electrical appliances. Commercial energy consumed outside of buildings and for combined heat and power is also included in the other category.
[11] Based on 2003 CBECS end-use-level consumption data developed using the methodology described in Estimation of Energy End-Use Intensities, web site www.eia.doe.gov/emeu/cbecs/tech_end_use.html.
[12] The proportion of equipment retiring is inversely related to the equipment life.
[13] Commercial pre-rinse spray valves are handheld devices used to remove food residue from dishes and "atware before cleaning.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 49
THIS PAGE INTENTIONALLY LEFT BLANK Industrial Demand Module THIS PAGE INTENTIONALLY LEFT BLANK Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-"ow or end-use accounting procedure, whereas the non-manufacturing industries are modeled with substantially less detail. The petroleum re"ning industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption to the nine Census Divisions based on "xed shares from the State Energy Data System [1].
Table 6.1. Industry categories Energy-Intensive Manufacturing Non-energy-Intensive Manufacturing Non-Manufacturing Food products (NAICS 311) Metal-based durables Agricultural crop Paper and allied products (NAICS 322) Fabricated metal products (NAICS 332) production (NAICS 111)
Bulk chemicals Machinery (NAICS 333)
Inorganic (NAICS 32512- Computer and electronic (NAICS 334) Other agricultural (NAICS 112, 32518) products production 113, 115)
Organic (NAICS 32511, Electrical equipment and (NAICS 335) Coal mining (NAICS 2121) 32519) appliances Resins (NAICS 3252) Transportation equipment (NAICS 336) Oil and gas extraction (NAICS 211)
Agricultural (NAICS 3253) Other Metal and other non- (NAICS 2122-Glass and glass products (NAICS 3272) Wood products (NAICS 321) metallic mining 2123)
(NAICS 32731, Plastic and rubber (NAICS 326) Construction (NAICS 23)
Cement and Lime 32741) products Iron and steel (NAICS 3311- Balance of manufacturing (all remaining 3312) manufacturing NAICS)
Aluminum (NAICS 3313)
NAICS = North American Industry Classi"cation System.
Source: Office of Management and Budget, North American Industry Classi"cation system (NAICS) - United States (Spring"eld, VA. National Technical Information Service).
The energy-intensive industries (food products, paper and allied products, bulk chemicals, glass and glass products, cement and lime, iron and steel, and aluminum) are modeled in considerable detail. Each industry is modeled as three separate but interrelated components: the Process and Assembly (PA) Component, the Buildings (BLD) Component, and the Boiler, Steam, and Cogeneration (BSC) Component. The BSC Component satis"es the steam demand from the PA and BLD Components. In some industries, the PA Component produces byproducts that are consumed in the BSC Component. For the manufacturing industries, the PA Component is separated into the major production processes or end uses. Petroleum re"ning (NAICS 32411) is modeled in detail in the Petroleum Market Module of NEMS, and the projected energy consumption is included in the manufacturing total. Projections of re"ning energy use, lease and plant fuel, and fuels consumed in cogeneration in the oil and gas extraction industry (NAICS 211) are exogenous to the Industrial Demand Module, but endogenous to the NEMS modeling system.
Key assumptions The NEMS Industrial Demand Module primarily uses a bottom-up process modeling approach. An energy accounting framework traces energy "ows from fuels to the industrys output. An important assumption in the development of this system is the use of 2006 baseline Unit Energy Consumption (UEC) estimates based on analysis and interpretations of the Manufacturing Energy Consumption Survey (MECS) 2006 conducted by the Energy Information Administration on a four-year survey cycle [2]. The UECs represent the energy required to produce one unit of the industrys output. The output may be de"ned in terms of physical units (e.g., tons of steel) or in terms of the dollar value of shipments.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 53
Industrial Demand Module The Industrial Demand Module depicts the manufacturing industries (apart from petroleum re"ning) with a detailed process "ow or end use approach. The dominant process technologies are characterized by a combination of unit energy consumption estimates and Technology Possibility Curves (TPC). With the exception of the cement and lime industries, the technology possibility curve is an exponential growth trend corresponding to a given average annual rate of change, orTPC. The TPC de"nes the assumed average annual rate of energy intensity change of a process step or an energy end use (e.g., generic heating or cooling). The TPCs for new and existing plants vary by industry, vintage and process. These assumed rates were developed using professional engineering judgments regarding the energy characteristics, year of availability, and rate of market adoption of new process technologies. For the cement and lime industry, energy projections are endogenously derived based on data obtained from the technology estimates (e.g., expenditures, energy coefficients, utility needs) in the Consolidated Impacts Modeling System (CIMS) database prepared by the Paci"c Northwest National Laboratory, as calibrated using inputs from the U.S. Geological Survey (USGS) of the U.S. Department of the Interior, Portland Cement Association and MECS 2006 released by EIA [3,4,5].
Process/assembly component The PA Component models each major manufacturing production step or end use for the manufacturing industries. The throughput production for each process step is computed, as well as the energy required to produce it. The unit energy coefficient (UEC) is de"ned as the amount of energy to produce a unit of output; it measures the energy intensity of the process or end use.
The module distinguishes the UECs by three vintages of capital stock. The amount of energy consumption re"ects the assumption that new vintage stock will consist of state-of-the-art technologies that have different efficiency than the existing capital stock. Consequently, the amount of energy required to produce a unit of output using new capital stock is often less than that required by the existing capital stock. The old vintage consists of capital existing in 2006 and surviving after adjusting for assumed retirements each year (Table 6.2). New production capacity is assumed to be added in a given projection year such that sufficient surviving and new capacity is available to meet the level of an industrys output as determined in the NEMS Regional Macroeconomic Module. Middle vintage capital is that which is added after 2006 up through the year prior to the current projection year.
To simulate technological progress and adoption of more-efficient energy technologies, the UECs are adjusted each projection year based on the assumed TPC for each step. The TPCs are derived from assumptions about the relative energy intensity (REI) of productive capacity by vintage (new capacity relative to existing stock in a given year) or over time (new or surviving capacity in 2035 relative to the 2006 stock). For example, state-of-the-art additions to steel hot rolling capacity in 2006 are assumed to require only 80 percent as much energy as does the average existing plant, so the REI for new capacity in 2006 is 0.80 (see Table 6.3). Over time, the UECs for new capacity change, and the rate of change is given by the TPC. The UECs of the surviving 2006 capital stock are also assumed to change over time, but not as rapidly as for new capital stock because of retro"tting. For example, with hot rolling, the TPC for new facilities is -0.008, while the TPC for existing facilities is -0.007. Table 6.3 provides more examples, including alternative assumptions used to re"ect an advanced, high tech case.
Table 6.2. Retirement rates Retirement Rate Retirement Rate Industry (percent) Industry (percent)
Food Products 1.7 Glass and Glass Products 1.3 Pulp and Paper 2.3 Cement and Lime Iron and Steel Kiln 1.2 Blast Furnace and Basic Steel Products 1.5 Finished Grinding 1.2 Electric Arc Furnace 1.5 Raw Grinding 2.4 Coke Oven 2.5 Aluminum 1.0 Other Steel 2.9 Metal-Based Durables 1.3 Bulk Chemicals 1.7 Other Non-intensive Manufacturing 1.3 Non-Manufacturing 1.0 Note: Except for the Blast Furnace and Basic Steel Products Industry, the retirement rate is the same for each process step or end-use within an industry.
Source: Energy Information Administration, Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System, DOE/
EIA-M064(2011), (Washington, DC, 2011).
54 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module The concepts of REI and TPCs are a means of embodying assumptions regarding new technology adoption in the manufacturing industry and the associated change in energy consumption of capital without characterizing individual technologies in detail. The approach re"ects the assumption that industrial plants will change energy consumption as owners replace old equipment with new, sometimes more-efficient equipment, add new capacity, add new products, or upgrade their energy management practices.
The reasons for the increased efficiency are not likely to be directly attributable to technology choice decisions, changing energy prices, or other factors readily subject to modeling. Instead, the module uses the REI and TPC concepts to characterize intensity trends for bundles of technologies available for major process steps or end use.
There are two exceptions to the general approach in the PA component. The "rst is for electric motor technology choice implemented for 9 industries to simulate their electric machine drive energy end use. Machine drive electricity consumption in the food industry, the "ve metal-based durables industries, and the three non-intensive manufacturing industries is calculated by a motor stock model. The beginning stock of motors is modi"ed over the projection horizon as motors are added to accommodate growth in shipments for each sector, as motors are retired and replaced, and as failed motors are rewound. When an old motor fails, an economic choice is made on whether to repair or replace the motor. When a new motor is added, either to accommodate growth or as a replacement, the motor must meet the minimum efficiency standard and a premium efficiency motor is also available. Table 6.4 provides the beginning stock efficiency for seven motor size groups in each of the three industry groups, as well as efficiencies for EPACT minimum and premium motors [7]. As the motor stock changes over the projection horizon, the overall efficiency of the motor population changes as well.
The second exception in the PA component is the Cement and Lime Submodel. The methodology is described below.
Cement and lime industry The addition of the cement and lime submodule is the "rst of several enhancements of the energy-intensive industries within the Industrial Demand Module. Instead of the aggregate energy intensity evolving according to TPC curves for both new and vintage equipment for the process "ows, the new submodule utilizes detailed technology choice for the process "ows. Data for existing equipment (capital and operating costs, energy use, and emissions) were obtained from the Consolidated Impacts Modeling System (CIMS) database. For the cement process "ow, each step (raw material grinding, kiln - both rotation and burner, "nished grinding) allows for multiple equipment choices whose fuel type and efficiency are known.
Cement has both dry and wet mill processes. Some technologies are available to both processes, while others are available to only one process. The technology choices within each group are:
- 1. Raw materials grinding: ball mill, roller mill
- 2. Kilns (rotators): rotary long with preheat, precalcining, and computer control (dry only), rotary preheat with high-efficiency cooler (dry only), rotary preheat, precalcine with efficient cooler (dry only), rotary wet standard with waste heat recovery boiler and cogeneration (wet only)
- 3. Kilns (burners): standard "red by natural gas, efficient "red by natural gas, standard "red by oil, efficient "red by oil, standard "red by coal, standard "red by petroleum coke, standard "red by hazardous waste, standard "red by residue-derived fuel
- 4. Finished grinders: standard ball mill, "nishing ball mill with high-efficiency separator, standard roller mill, "nishing roller mill with high-efficiency separator The equipment slate in each of these process steps evolves over time and depends on the relative cost of equipment, cost of fuel, and fuel efficiency. The base year equipment slate is determined from the latest CIMS database and calibrated for the base year 2006 with dry and wet mill capacity cement fuel use data from the Portland Cement Association, the USGS, and the 2006 MECS. All new cement capacity, both for replacement and increased production, is assumed to be dry cement capacity. Existing wet capacity is assumed to retire at a linear rate over 20 years with no replacement. Imported clinker, additives, and "y-ash are assumed to make constant percentage contributions to the "nished product and thus displace a certain amount of domestic clinker production, and therefore energy use.
Lime shipments are estimated using a "xed percentage of stone, clay and glass shipments. Lime shipments, plus cement shipments, are presented together as the consolidated cement and lime output. Energy consumption and equipment evolution in the lime industry are driven by the same methods implemented for cement, with different, industry-speci"c equipment choices.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 55
Industrial Demand Module
+- P ! &"& "$ 4 - "4& "
Existing Facilities New Facillities High High High High Reference Tech REI Reference Tech REI Reference Tech REI Reference Tech Industry/Process Unit REI20401 20401 TPC%2 TPC%2 20063 REI20404 20404 TPC%2 TPC%2 Food Products Process Heating 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094 Process Heating-Steam 0.747 0.940 -0.853 -0.182 0.900 0.650 0.792 -0.953 -0.375 Process Cooling-Electricity 0.832 0.981 -0.540 -0.057 0.850 0.715 0.822 -0.506 -0.100 Process Cooling-Natural Gas 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094 Other-Electricity 0.883 0.987 -0.364 -0.039 0.915 0.773 0.885 -0.493 -0.097 Other-Natural Gas 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094 Paper & Allied Products Wood Preparation 0.760 0.989 -0.802 -0.033 0.882 0.674 1.006 -0.790 -0.386 Waste Pulping-Electricity 0.925 0.947 -0.228 -0.161 0.936 0.936 0.866 0.000 -0.228 Waste Pulping-Steam 0.856 0.896 -0.456 -0.322 0.936 0.936 0.801 0.000 -0.456 Mechanical Pulping-Electricity 0.770 1.007 -0.767 0.021 0.931 0.580 1.259 -1.380 0.893 Mechanical Pulping-Steam 0.591 1.015 -1.533 0.043 0.931 0.359 1.699 -2.760 1.787 Semi-Chemical-Electricity 0.943 0.991 -0.173 -0.025 0.971 0.923 0.954 -0.149 -0.052 Semi-Chemical-Steam 0.889 0.983 -0.346 -0.051 0.971 0.877 0.937 -0.297 -0.105 Kraft, Sul"te, Misc. Chemicals 0.838 0.919 -0.519 -0.249 0.914 0.793 0.770 -0.415 -0.502 Kraft, Sul"te, Misc Chemicals-Steam 0.701 0.844 -1.037 -0.498 0.914 0.688 0.648 -0.830 -1.004 Bleaching-Electricity 0.747 0.918 -0.853 -0.252 0.878 0.651 0.918 -0.878 0.129 Bleaching-Steam 0.557 0.842 -1.706 -0.504 0.878 0.481 0.959 -1.756 0.259 Paper Making 0.848 0.802 -0.485 -0.621 0.885 0.846 0.553 -0.132 -1.376 Paper Making-Steam 0.944 0.809 -0.969 -0.621 0.885 0.809 0.553 -0.264 -1.376 Bulk Chemicals Process Heating 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149 Process Heating-Steam 0.590 0.721 -1.541 -0.957 0.724 0.377 0.481 -1.904 -1.194 Process Heating-Natural Gas 0.769 0.922 -0.770 -0.239 0.724 0.523 0.654 -0.952 -0.298 Process Cooling-Electricity 0.832 0.945 -0.540 -0.168 0.850 0.715 0.805 -0.506 -0.159 Process Cooling-Natural Gas 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149 Electro-Chemicals 0.972 0.991 -0.082 -0.025 0.950 0.815 0.905 -0.450 -0.141 Other 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149 Other-Electricity 0.883 0.962 -0.364 -0.113 0.915 0.773 0.868 -0.493 -0.155 Other-Natural Gas 0.769 0.922 -0.770 -0.239 0.724 0.523 0.654 -0.952 -0.298 Glass and Glass Products5 Batch Preparation-Electricity 0.931 1.000 -0.209 0.000 0.882 0.882 0.882 0.000 0.000 Melting/Re"ning 0.923 0.822 -0.235 -0.576 0.900 0.863 0.561 -0.125 -1.381 Melting/Re"ning-Steam 0.852 0.675 -0.470 -0.151 0.900 0.827 0.347 -0.250 -2.761 Forming 0.981 0.971 -0.056 -0.085 0.982 0.966 0.925 -0.048 -0.175 Forming-Steam 0.963 0.944 -0.111 -0.170 0.982 0.950 0.871 -0.096 -0.350 Post-Forming 0.974 0.989 -0.078 -0.034 0.968 0.953 0.945 -0.045 -0.069 Post-Forming-Steam 0.948 0.977 -0.157 -0.067 0.968 0.938 0.923 -0.090 -0.139 Cement & Lime Dry Process 0.867 0.849 -0.420 -0.479 0.885 0.752 0.584 -0.479 -1.216 6
Wet Process 0.935 0.920 -0.197 -0.245 NA NA NA NA NA Wet Process-Steam 0.874 0.685 -0.395 -1.107 NA NA NA NA NA Finish Grinding-Electricity 0.971 0.828 -0.087 -0.554 0.950 0.950 0.620 0.000 -1.248 56 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module
+- P ! &"& "$ 4 - "4& " V " W
Existing Facilities New Facillities High High High High Reference Tech REI Reference Tech REI Reference Tech REI Reference Tech Industry/Process Unit REI20401 20401 TPC%2 TPC%2 20063 REI20404 20404 TPC%2 TPC%2 Iron and Steel Coke Oven 0.924 0.864 -0.233 -0.429 0.902 0.863 0.624 -0.128 -1.076 Coke Oven-Steam 0.853 0.746 -0.467 -0.858 0.902 0826 0.431 -0.257 -2.152 BF/BPF 0.992 0.943 -0.022 -0.172 0.987 0.987 0.869 0.000 -0.375 BF/BOF-Steam 0.985 0.889 -0.045 -0.345 0.987 0.987 0.764 0.000 -0.751 EAF 0.901 0.889 -0.308 -0.346 0.990 0.805 0.750 -0.606 -0.813 Ingot Casting/Primary Rolling 1.000 1.000 0.000 0.000 NA NA NA NA NA Continuous Casting 1.000 1.000 0.000 0.000 1.000 1.000 1.000 0.000 0.000 Hot Rolling7 0.788 0.890 -0.699 -0.344 0.800 0.608 0.573 0.804 -0.978 7
Hot Rolling-Steam 0.620 0.791 -1.397 -0.687 0.800 0.461 0.409 -1.608 -1.956 Cold Rolling7 0.677 0.940 -1.141 -1.183 0.924 0.380 0.842 -2.580 -0.273 Cold Rolling-Steam7 0.456 0.883 -2.281 -0.365 0.924 0.153 0.767 -5.160 -0.546 Aluminum Alumina Re"ning 0.915 0.979 -0.262 -0.063 0.900 0.846 0.859 -0.182 -0.138 Alumnina Re"ning-Steam 0.837 0.722 -0.524 -0.952 0.900 0.795 0.395 -0.365 -2.395 Primary Smelting 0.872 0.850 -0.401 -0.476 0.950 0.754 0.631 -0.678 -1.198 Primary Smelting-Steam 0.760 0.722 -0.802 -0.952 0.950 0.597 0.417 -1.355 -2.395 Secondary 0.847 0.922 -0.487 -0.238 0.850 0.718 0.695 -0.495 -0.590 Semi-fabrication, Steel 0.876 0.778 -0.389 -0.735 0.900 0.768 0.464 -0.466 -1.927 Semi-Fabrication, Other 0.905 0.854 0.295 0.465 0.950 0.818 0.650 -0.440 -1.109 Metal-Based Durables Fabricated Metals Process Heating 0.613 0.605 -1.427 -1.468 0.675 0.366 0.299 -1.784 -2.370 Process Cooling-Electricity 0.680 0.536 -1.127 -1.820 0.638 0.332 0.270 -1.903 -2.493 Process Cooling-Natural Gas 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370 Other 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370 Other-Electricity 0.680 0.647 -1.127 -1.274 0.686 0.366 0.296 -1.834 -2.439 Machinery Process Heating 0.613 0.605 -1.427 -1.468 0.675 0.366 0.299 -1.784 -2.370 Process Cooling-Electricity 0.680 0.536 -1.127 -1.820 0.638 0.332 0.270 -1.903 -2.493 Process Cooling-Natural Gas 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370 Other 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370 Other-Electricity 0.680 0.647 -1.127 -1.274 0.686 0.366 0.296 -1.834 -2.439 Computers and Electronics Process Heating 0.722 0.716 -0.952 -0.979 0.720 0.531 0.480 -0.892 -1.185 Process Cooling-Electricity 0.774 0.660 -0.751 -1.213 0.680 0.491 0.444 -0.952 -1.247 Process Cooling-Natural Gas 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185 Other 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185 Other-Electricity 0.774 0.748 -0.751 -0.850 0.732 0.535 0.482 -0.917 -1.219 Electrical Equipment Process Heating 0.722 0.716 -0.952 -0.979 0.720 0.531 0.480 -0.892 -1.185 Process Heating-Steam NA NA -1.502 -3.914 NA NA NA -1.679 -4.740 Process Cooling-Electricity 0.774 0.660 -0.751 -1.213 0.680 0.491 0.444 -0.952 -1.247 Process Cooling-Natural Gas 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185 Other 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185 Other-Electricity 0.774 0.748 -0.751 -0.850 0.732 0.535 0.482 -0.917 -1.219 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 57
Industrial Demand Module
+- P ! &"& +$ 4 - "4!& :" X V " W
Existing Facilities New Facillities High High High High Reference Tech REI Reference Tech REI Reference Tech REI Reference Tech Industry/Process Unit REI20401 20401 TPC%2 TPC%2 20063 REI20404 20404 TPC%2 TPC%2 Transportation Equipment Processing Heating 0.797 0.608 -0.666 -0.685 0.765 0.600 0.553 -0.714 -0.948 Processing Heating-Steam 0.698 0.386 -1.052 -2.740 0.765 0.483 0.389 -1.343 -3.792 Process Cooling-Electricity 0.836 0.539 -0.526 -0.849 0.723 0.557 0.514 -0.761 -0.997 Process Cooling-Natural Gas 0.836 0.608 -0.526 -0.685 0.765 0.608 0.553 -0.672 -0.948 Other 0.836 0.647 -0.526 -0.685 0.765 0.608 0.553 -0.672 -0.948 Other-Electricity 0.836 0.860 -0.526 -0.595 0.778 0.606 0.557 -0.734 -0.975 Other Non-Intensive Manufacturing Wood Products Process Heating 0.613 0.654 -1.427 -1.452 0.630 0.342 0.342 -1.784 -2.358 Process Heating-Steam 0.720 0.426 -2.253 -5.807 0.630 0.386 0.386 -3.358 -9.432 Process Cooling-Electricity 0.680 0.590 -1.127 -1.804 0.595 0.310 0.310 -1.903 -2.481 Process Cooling-Natural Gas 0.680 0.654 -1.127 -1.452 0.630 0.354 0.354 -1.679 -2.358 Other 0.680 0.690 -1.127 -1.272 0.630 0.354 0.354 -1.679 -2.209 Other-Electricity 0.683 0.879 -1.115 -0.443 0.641 0.373 0.340 -1.845 -2.388 Plastic Products Process Heating 0.722 0.718 -0.952 -0.968 0.675 0.498 0.451 -0.892 -1.179 Process Heating-Steam 0.598 0.380 -1.502 -3.871 0.675 0.380 0.380 -1.679 -4.716 Process Cooling-Electricity 0.774 0.663 -0.751 -1.203 0.638 0.461 0.417 -0.952 -1.241 Process Cooling-Natural Gas 0.774 0.718 -0.751 -0.968 0.675 0.507 0.451 -0.840 -1.179 Other 0.774 0.749 -0.751 -0.848 0.675 0.507 0.463 -0.840 -1.104 Other-Electricity 0.776 0.904 -0.743 -0.295 0.686 0.501 0.456 -0.922 -1.194 Balance of Manufacturing Process Heating 0.784 0.781 -0.714 -0.726 0.675 0.529 0.489 -0.714 -0.943 Process Heating-Steam 0.903 0.589 -0.600 -1.546 0.900 0.762 0.348 -0.980 -2.753 Process Cooling-Electricity 0.825 0.735 -0.563 -0.902 0.638 0.492 0.454 -0.761 -0.992 Process Cooling-Natural Gas NA NA -0.563 -0.726 NA NA NA -0.672 -0.943 Other Natural Gas 0.825 0.805 -0.563 -0.636 0.675 0.537 0.499 -0.672 -0.883 1
REI 2040 Existing Facilities = Ratio of 2040 energy intensity to average 2006 energy intensity for existing facilities.
2 TPC = annual rate of change between 2006 and 2035.
3 REI 2006 New Facilities = For new facilities, the ratio of state-of-the-art energy intensity to average 2006 energy intensity for existing facilities.
4 REI 2040 New Facilities = Ratio of 2040 energy intensity for a new state-of-the-art facility to the average 2006 intensity for existing facilities.
5 REIs and TPCs apply to virgin and recycled materials.
6 No new plants are likely to be built with these technologies.
7 Net shape casting is projected to reduce the energy requirements for hot and cold rolling rather than for the continuous casting step.
NA = Not applicable.
BF = Blast furnace.
BOF = Basic oxygen furnace.
EAF = Electric arc furnace.
Source: U.S. Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System, DOE/
EIA-M064(2011) (Washington, DC, 2011).
58 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module
+- P ' ! "& 66"& " 6 " $ 6
Premium Industrial Sector Base Stock Premium Cost Horsepower Range Efficiency (%) Efficiency (%) (2002$)
Food 1-5 hp 86.7 89.2 601 6 - 20 hp 91.2 92.5 1,338 21 - 50 hp 93.0 93.8 2,585 51 - 100 hp 94.0 95.3 6,290 101 - 200 hp 94.6 95.2 11,430 201 - 500 hp 93.6 95.4 29,991
> 500 hp 94.1 96.2 36,176 1
Metal-Based Durables 1-5 hp 86.7 89.2 601 6-20 hp 91.3 92.5 1,338 21-50 hp 93.0 93.9 2,585 51-100 hp 94.0 95.3 6,290 101-200 hp 94.6 95.2 11,430 201-500 hp 93.7 95.4 29,991
>500 hp 94.1 96.2 36,176 2
Other Non-Intensive Manufacturing 1-5 hp 86.7 89.2 601 6-20 hp 91.3 92.5 1,338 21-50 hp 93.0 93.9 2,585 51-100 hp 94.0 95.3 6,290 101-200 hp 94.6 95.2 11,430 201-500 hp 93.7 95.4 11,430
>500 hp 94.1 96.2 36,176 1
The Metal-Based Durables group includes "ve industries that are modeled separately: Fabricated Metal Products; Machinery; Computer and Electronic Products; Electrical Equipment, Appliances, and Components; and Transportation Equipment.
2 The Other Non-Intensive Manufacturing group includes three sectors that are modeled separately: Wood Products; Plastics and Rubber Products; and Balance of Manufacturing.
Source: U.S. Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System, DOE/EIA-M064(2011) (Washington, DC, 2011).
Note: The efficiencies listed in this table are operating efficiencies based on average part-loads. Because the average part-load is not the same for all industries, the listed efficiencies for the different motor sizes vary across industries.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 59
Industrial Demand Module
" $6 &" @#6"
This subroutine estimates feedstock requirements for the major petrochemical intermediates such as ethylene, propylene, and butadiene. The primary feedstocks used to produce these chemicals are natural gas liquids (NGLs) (ethane, propane, butane) and petrochemical (oil-based) feedstocks (gas oil, naphtha) [6]. Biomass is a potential raw material source, but it is assumed that there will be no biomass-based capacity over the projection period because of economic barriers. The type of feedstock not only determines the source of feedstock but also the energy for heat and power requirements to produce the chemicals.
To determine the relative amounts of feedstock (NGLs or oil-based) baseline intensities, feedstock consumption intensities are derived from the 2006 MECS. Feedstock consumption of both types grows or declines with organic chemicals shipment value.
It should be noted that there is no change in the feedstock intensity over time, i.e., all feedstock TPCs are assumed to be zero.
Unlike most other processes represented in manufacturing PA components, chemical yields are governed by basic chemical stoichiometry which allows for speci"c yields under set conditions of pressure and temperature. For the projected LPG feedstock quantities, a further subdivision is made into re"nery-produced propylene and ethane (all ethane produced by the NEMS Oil and Gas Supply Module is absorbed by the chemical model). The remaining balance of LPG feedstock requirement is a mixture of pentanes plus, butane, and propane.
Buildings component The total buildings energy demand by industry for each region is a function of regional industrial employment and output.
Building energy consumption was estimated for building lighting, HVAC (heating, ventilation, and air conditioning), facility support, and on-site transportation. Space heating was further divided to estimate the amount provided by direct combustion of fossil fuels and that provided by steam (Table 6.5). Energy consumption in the BLD Component for an industry is estimated based on regional employment and output growth for that industry using the 2006 MECS as a basis.
Boiler, steam, and cogeneration component The steam demand and byproducts from the PA and BLD Components are passed to the BSC Component, which applies a heat rate and a fuel share equation (Table 6.6) to the boiler steam requirements to compute the required energy consumption.
The boiler fuel shares apply only to the fuels that are used in boilers for steam-only applications. Fuel use for the portion of the steam demand associated with combined heat and power (CHP) is described in the next section. Some fuel switching for the remainder of the boiler fuel use is assumed and is calculated with a logit-sharing equation where fuels shares are a function of fuel prices. The equation is calibrated to 2006 so that the 2006 fuel shares are produced for the relative prices that prevailed in 2006.
The byproduct fuels, production of which is estimated in the PA Component, are assumed to be consumed without regard to price, independent of purchased fuels. The boiler fuel share equations and calculations are based on the 2006 MECS and information from the Council of Industrial Boiler Owners.[8]
! 6-$" /
CHP plants, which are designed to produce both electricity and useful heat, have been used in the industrial sector for many years. The CHP estimates in the module are based on the assumption that the historical relationship between industrial steam demand and CHP will continue in the future, and that the rate of additional CHP penetration will depend on the economics of retro"tting CHP plants to replace steam generated from existing non-CHP boilers. The technical potential for CHP is primarily based on supplying thermal requirements (i.e., matching thermal loads). Capacity additions are then determined by the interaction of CHP investment payback periods (with the time-value of money included) derived using operating hours reported in EIAs published statistics, market penetration rates for investments with those payback periods, and regional deployment for these systems as characterized by the collaboration coefficients in Table 6.8. Assumed installed costs for the CHP systems are given in Table 6.7.
60 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module Table 6.5. 2006 Building component energy consumption trillion Btu Building Use and Energy Source Facility Onsite Lighting HVAC HVAC HVAC Support Transportation Electricity Electricity Natural Gas Steam Total Total Industry Region Consumption Consumption Consumption Consumption Consumption Consumption Food Products 1 1.5 1.7 1.7 1.2 1.0 0.6 2 8.3 9.1 14.9 5.3 7.0 1.2 3 6.5 7.1 8.7 6.0 4.6 1.3 4 3.5 3.9 7.0 4.8 3.3 1.5 Paper & Allied Products 1 1.6 1.8 2.6 0.0 0.7 1.8 2 3.7 4.1 2.9 0.0 1.2 1.3 3 8.7 9.8 9.5 0.0 3.0 4.2 4 3.9 4.4 2.9 0.0 1.3 1.8 Bulk Chemicals 1 1.0 1.3 1.6 0.0 1.1 1.9 2 2.9 3.8 4.2 0.0 3.1 4.1 3 11.1 14.5 11.5 0.0 10.6 6.8 4 1.1 1.5 1.7 0.0 1.3 2.0 Glass & Glass Products 1 0.4 0.3 3.4 0.0 2.2 2.5 2 1.2 1.0 5.8 0.0 2.7 2.8 3 1.1 0.9 6.1 0.0 2.7 2.7 4 0.3 0.3 3.1 0.0 2.1 2.5 Cement 1 0.2 0.4 0.7 0.0 0.6 0.7 2 0.5 0.8 0.7 0.0 1.0 1.4 3 0.7 1.1 0.8 0.0 1.1 2.3 4 0.5 0.7 0.6 0.0 0.9 1.4 Iron and Steel 1 1.0 0.8 2.6 0.0 0.8 0.7 2 2.6 2.0 8.8 0.0 1.5 1.9 3 2.7 2.0 3.6 0.0 1.1 1.2 4 0.4 0.3 1.3 0.0 0.6 0.7 Aluminum 1 0.4 0.2 0.6 0.0 0.4 0.2 2 0.5 0.3 1.1 0.0 0.5 0.2 3 1.9 1.2 2.8 0.0 1.6 0.7 4 0.3 0.2 0.4 0.0 0.3 0.2 Metal-Based Durables Fabricated Products 1 1.8 1.8 4.7 4.0 0.7 0.4 2 5.9 5.9 18.7 15.9 2.5 2.0 3 4.7 4.7 11.9 10.0 1.9 2.3 4 1.8 1.8 2.5 2.1 0.6 0.5 Machinery 1 2.5 1.8 4.7 4.0 0.7 0.4 2 9.5 5.9 18.7 15.9 2.5 2.0 3 3.7 4.7 11.9 10.0 1.9 2.3 4 0.7 1.8 2.5 2.1 0.6 0.5 Computers & Electronic Products 1 2.0 4.8 4.4 3.9 1.7 0.6 2 1.7 4.0 4.6 4.0 1.5 0.6 3 3.1 7.3 4.2 3.6 2.3 0.6 4 4.3 10.2 7.2 6.5 3.0 0.6 Electrical Equipment 1 3.5 4.5 11.6 0.9 1.3 0.4 2 15.2 19.9 56.2 4.2 5.8 2.1 3 8.0 10.4 14.1 1.1 2.6 1.2 4 2.7 3.5 6.9 0.4 0.9 0.5 Transportation Equipment 1 0.6 0.7 0.7 0.5 0.2 0.3 2 1.7 2.1 2.4 1.9 0.8 0.5 3 2.5 3.0 4.8 3.7 1.2 0.6 4 0.2 0.3 0.5 0.4 0.1 0.3 Other Non-Intensive Manufacturing Wood Products 1 0.5 0.3 0.5 0.9 0.1 0.9 2 2.1 1.5 3.0 5.8 0.6 4.2 3 2.3 2.3 1.9 3.7 0.7 5.0 4 1.4 1.0 1.7 3.3 0.4 4.2 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 61
Industrial Demand Module
+- P PZ 6 "4 6" V " W
trillion Btu Building Use and Energy Source Facility Onsite Lighting HVAC HVAC HVAC Support Transportation Electricity Electricity Natural Gas Steam Total Total Industry Region Consumption Consumption Consumption Consumption Consumption Consumption Plastic Products 1 2.0 2.5 4.3 0.0 1.2 1.3 2 7.0 8.7 9.6 0.0 3.1 1.0 3 5.9 7.4 11.2 0.0 2.9 1.0 4 1.1 1.4 0.8 0.0 0.5 0.3 Balance of Manufacturing 1 5.7 8.8 14.9 0.0 2.3 1.9 2 16.7 25.8 23.1 0.0 6.1 1.3 3 21.4 33.0 43.7 0.0 8.3 2.1 4 4.0 6.1 11.1 0.0 1.7 0.9 HVAC = Heating, Ventilation, Air Conditioning.
Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling System, DOE/EIA-M064(2011) (Washington, DC 2011).
62 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module Table 6.6. 2006 Boiler fuel component and logit parameter trillion Btu Region Alpha Natural Gas Coal Oil Renewables Food Products 1 -2.0 19 0 4 1 2 -2.0 168 109 12 22 3 -2.0 96 11 12 52 4 -2.0 76 14 4 4 Paper & Allied Products 1 -2.0 41 40 16 80 2 -2.0 48 60 12 90 3 -2.0 159 91 64 998 4 -2.0 53 13 4 97 Bulk Chemicals 1 -2.0 13 0 56 0 2 -2.0 97 37 18 0 3 -2.0 605 31 384 0 4 -2.0 20 21 6 0 Glass & Glass Products 1 -2.0 2 0 3 10 2 -2.0 6 0 3 1 3 -2.0 6 0 3 2 4 -2.0 1 0 3 1 Cement 1 -2.0 0 0 1 1 2 -2.0 1 0 1 5 3 -2.0 0 0 1 3 4 -2.0 0 0 1 3 Iron & Steel 1 -2.0 4 6 20 0 2 -2.0 16 1 66 0 3 -2.0 6 0 7 0 4 -2.0 1 0 1 0 Aluminum 1 -2.0 2 0 0 0 2 -2.0 4 0 0 0 3 -2.0 11 0 0 0 4 -2.0 1 0 0 0 Metal-Based Durables Fabricated Metal Products 1 -2.0 4 0 1 0 2 -2.0 5 0 1 0 3 -2.0 4 0 1 0 4 -2.0 8 0 1 1 Machinery 1 -2.0 3 0 1 0 2 -2.0 12 1 0 1 3 -2.0 5 0 0 0 4 -2.0 1 0 0 0 Computers & electronic Products 1 -2.0 4 0 1 0 2 -2.0 5 0 1 0 3 -2.0 4 0 1 0 4 -2.0 8 0 1 1 Electrical Equipment 1 -2.0 6 8 3 7 2 -2.0 27 -3 1 5 3 -2.0 7 1 3 4 4 -2.0 3 0 0 0 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 63
Industrial Demand Module
+- P P PZ & 6 " "6"V " W
trillion Btu Region Alpha Natural Gas Coal Oil Renewables Transportation Equipment 1 -2.0 1 0 0 0 2 -2.0 2 0 0 0 3 -2.0 4 0 0 0 4 -2.0 0 0 0 0 Other Non-Intensive Manufacturing Wood Products 1 -2.0 2 0 0 11 2 -2.0 12 1 1 40 3 -2.0 7 0 1 123 4 -2.0 5 0 2 48 Plastic Products 1 -2.0 10 0 2 0 2 -2.0 23 0 0 0 3 -2.0 25 10 6 0 4 -2.0 2 0 0 0 Balance of Manufacturing 1 -2.0 41 -11 18 1 2 -2.0 64 51 28 2 3 -2.0 121 58 31 22 4 -2.0 31 8 15 0 Alpha: User-speci"ed.
Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling System, DOE/EIA-M064(2011) (Washington, DC 2011).
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Installed Cost Size Kilowatts (2005$ per KWh)1 System (KW) Reference 2010 Reference 2035 High Tech 2035 Engine 100 1440 576 535 300 1260 396 354 Gas turbine 3000 1719 1496 1450 5000 1152 1023 1006 10000 982 869 869 25000 987 860 860 40000 875 830 830 Combined cycle 100000 723 684 668 1
Costs are given in 2005 dollars in original source document.
Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling System, DOE/EIA-M064(2011) (Washington, DC 2011).
+- P 7 % - " &"& !\ 46"
Census Region Collaboration Coefficient Northeast 1.46 Midwest 1.34 South 0.33 West 1.06 Source: American Council for an Energy-Efficient Economy, Challenges Facing Combined Heat and Power Today: A State-by-State Assessment, September 2011, website: www.aceee.org/research-report/ie111 and Energy Information Administration, Office of Energy Analysis.
64 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Industrial Demand Module Legislation and regulations Energy Improvement and Extension Act of 2008 Under EIEA2008 Title I, Energy Production Incentives, Section 103 provides an Investment Tax Credit (ITC) for qualifying Combined Heat and Power (CHP) systems placed in service before January 1, 2017. Systems with up to 15 megawatts of electrical capacity qualify for an ITC up to 10 percent of the installed cost. For systems between 15 and 50 megawatts, the percentage tax credit declines linearly with the capacity, from 10 percent to 3 percent. To qualify, systems must exceed 60-percent fuel efficiency, with a minimum of 20 percent each for useful thermal and electrical energy produced. The provision was modeled in AEO2012 by adjusting the assumed capital cost of industrial CHP systems to re"ect the applicable credit.
The Energy Independence and Security Act of 2007 Under EISA2007, the motor efficiency standards established under the Energy Policy Act of 1992 (EPACT) are superseded for purchases made after 2011. Section 313 of EISA2007 increases or creates minimum efficiency standards for newly manufactured, general purpose electric motors. The efficiency standards are raised for general purpose, integral-horsepower induction motors with the exception of "re pump motors. Minimum standards were created for seven types of poly-phase, integral-horsepower induction motors and NEMA design B motors (201-500 horsepower) that were not previously covered by EPACT standards. The industrial modules motor efficiency assumptions re"ect the EISA2007 efficiency standards for new motors added after 2011.
Energy Policy Act of 1992 (EPACT)
EPACT contains several implications for the industrial module. These implications concern efficiency standards for boilers, furnaces, and electric motors. The industrial module uses heat rates of at least 1.25 (80 percent efficiency) and 1.22 (82 percent efficiency) for gas and oil burners, respectively. These efficiencies meet the EPACT standards. EPACT mandates minimum efficiencies for all motors up to 200 horsepower purchased after 1998. The choices offered in the motor efficiency assumptions are all at least as efficient as the EPACT minimums.
Clean Air Act Amendments of 1990 (CAAA90)
The CAAA90 contains numerous provisions that affect industrial facilities. Three major categories of such provisions are as follows: process emissions, emissions related to hazardous or toxic substances, and SO2 emissions.
Process emissions requirements were speci"ed for numerous industries and/or activities (40 CFR 60). Similarly, 40 CFR 63 requires limitations on almost 200 speci"c hazardous or toxic substances. These speci"c requirements are not explicitly represented in the NEMS industrial model because they are not directly related to energy consumption projections.
Section 406 of the CAAA90 requires the Environmental Protection Agency (EPA) to regulate industrial SO2 emissions at such time that total industrial SO2 emissions exceed 5.6 million tons per year (42 USC 7651). Since industrial coal use, the main source of SO2 emissions, has been declining, EPA does not anticipate that speci"c industrial SO2 regulations will be required (Environmental Protection Agency, National Air Pollutant Emission Trends: 1990-1998, EPA-454/R-00-002, March 2000, Chapter 4). Further, since industrial coal use is not projected to increase, the industrial cap is not expected be a factor in industrial energy consumption projections. (Emissions due to coal-to-liquids CHP plants are included with the electric power sector because they are subject to the separate emission limits of large electricity generating plants.)
- " ""
Technology cases The Industrial Demand Module High Technology case inputs assume earlier availability, lower costs, and higher efficiency of more advanced equipment, based on engineering judgments and research compiled by Focis Associates in a 2005 study for EIA (Tables 6.3 and 6.7) [9]. The High Technology case inputs also assume that the rate at which biomass byproducts will be recovered from industrial processes increases from 0.4 percent per year to 0.7 percent per year. The availability of additional biomass leads to an increase in biomass-based cogeneration. Changes in aggregate energy intensity can result both from changing equipment and production efficiency and from changes in the composition of industrial output.
The Industrial Demand Module 2011 Technology case inputs hold the energy efficiency of plant and equipment constant at the 2012 level over the projection period.
AEO2012 includes an Integrated High Technology case, which combines the High Technology inputs of all four end-use demand sectors, and assumes that costs for new nuclear and fossil-"red power plants are 20 percent below the Reference level in 2012 and 40 percent below by 2035.
The Low Renewable Technology Cost case assumes that the rate at which biomass byproducts will be recovered from industrial processes increases to 1.3 percent per year. The availability of additional biomass leads to an increase in biomass-based CHP.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 65
Industrial Demand Module Notes and sources
[1] U.S. Energy Information Administration, State Energy Data System, based on energy consumption by State through 2009, as downloaded in August, 2011, from www.eia.gov/state/seds/.
[2] U. S. Energy Information Administration, Manufacturing Energy Consumption Survey, website www.eia.doe.gov/
emeu/mecs/.
[3] Roop, Joseph M. The Industrial Sector in CIMS-US, Paci"c Northwest National Laboratory, 28th Industrial Energy Technology Conference, May, 2006.
[4] Portland Cement Association, U.S. and Canadian Portland Cement Industry Plant Information Summary, cement data was made available under a non-disclosure agreement, website www.cement.org/.
[5] U.S. Department of the Interior, U.S. Geological Survey, Minerals Yearbook, cement data was made available under a non-disclosure agreement, website www.minerals.usgs.gov/minerals/pubs/commodity/cement/.
[6] In NEMS, NGLs are reported as Lique"ed Petroleum Gas (LPG).
[7] U.S., Department of Energy(2007). Motor Master+ 4.0 software database; available at updated link www1.eere.
energy.gov/manufacturing/tech_deployment/software_motormaster.html.
[8] Personal correspondence with the Council of Industrial Boiler Owners.
[9] U.S. Energy Information Administration, Industrial Technology and Data Analysis Supporting the NEMS Industrial Model (Focis Associates, October 2005).
66 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand THIS PAGE INTENTIONALLY LEFT BLANK Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-speci"c and associated technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes:
light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks
(>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight and passenger rail, freight shipping, and miscellaneous transport such as recreational boating. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial "eet consumption.
Key assumptions Light-duty vehicle assumptions The light-duty vehicle Manufacturers Technology Choice Model (MTCM) includes 58 advanced technology input assumptions speci"c to cars and light trucks (Tables 7.1 and 7.2) that include incremental fuel economy improvement, incremental cost, "rst year of introduction, and fractional horsepower change.
The vehicle sales share module holds the share of vehicle sales by manufacturers constant within a vehicle size class at 2008 levels based on National Highway Traffic and Safety Administration (NHTSA) data [1]. Environmental Protection Agency (EPA) size class sales shares are projected as a function of income per capita, fuel prices, and average predicted vehicle prices based on endogenous calculations within the MTCM [2] .
The MTCM utilizes 58 new technologies for each size class and manufacturer based on the cost-effectiveness of each technology and an initial availability year. The discounted stream of fuel savings is compared to the marginal cost of each technology to determine cost effectiveness and market penetration. The fuel economy module assumes the following:
t The "nancial parameters used to determine technology economic effectiveness are evaluated based on the need to improve fuel economy to meet CAFE standards versus consumer willingness to pay for fuel economy improvement beyond those minimum requirements.
t Fuel economy standards for light duty vehicles re"ect current law through model year 2016, according to NHTSA model year 2011 "nal rulemaking and joint EPA and NHTSA rulemaking for 2012 through 2016. For model years 2017 through 2020, the standards re"ect EIA assumed increases that ensure a light vehicle combined fuel economy of 35 miles per gallon (mpg) is achieved by model 2020. For model years 2021 through 2035, fuel economy standards are held constant at model year 2020 levels with fuel economy improvements still possible based on continued improvements in economic effectiveness.
t Expected future fuel prices are calculated based on an extrapolation of the growth rate between a "ve-year moving average of fuel price 3 years and 4 years prior to the present year. This assumption is founded upon an assumed lead time of 3 to 4 years to signi"cantly modify the vehicles offered by a manufacturer.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 69
Transportation Demand Module Table 7.1. Standard technology matrix for cars1 Per Unit Absolute Incremental Fuel Incremen- Incremen- Weight Introduc-Efficiency Incremental Cost tal Cost tal Weight (Lbs./Unit tion Horsepower Change % (2000$) ($/Unit Wt.) (Lbs.) Wt.) Year Change %
Unit Body Construction 4.0 100.0 0 0 -6.0 1980 0 Material Substitution II 3.3 0 0.4 0 -5.0 1990 0 Material Substitution III 6.6 0 0.6 0 -10.0 1998 0 Material Substitution IV 9.9 0 0.9 0 -15.0 2006 0 Material Substitution V 13.2 0 1.2 0 -20.0 2014 0 Drag Reduction II 1.5 16.0 0 0 0 1988 0 Drag Reduction III 3.0 32.0 0 0 0.2 1992 0 Drag Reduction IV 4.2 45.0 0 0 0.5 2000 0 Drag Reduction V 5.0 53.5 0 0 1.0 2010 0 Adv Low Loss Torque Converter 2.0 25.0 0 0 0 1999 0 Early Torque Converter Lockup 0.5 25.6 0 0 0 2002 0 Aggressive Shift Logic 1.5 30.5 0 0 0 1999 0 4-Speed Automatic 4.5 285 0 10 0 1980 0 5-Speed Automatic 2.5 90.0 0 20 0 1995 0 6-Speed Automatic 5.5 170.0 0 30 0 2003 0 6-Speed Manual 0.5 91.4 0 20 0 1995 0 CVT 5.0 222.0 0 -25 0 1998 0 Automated Manual Trans 10.1 109.0 0 0 0 2004 0 Roller Cam 2.0 16.0 0 0 0 1980 0 OHC/AdvOHV-4 Cylinder 2.0 99.0 0 0 0 1980 2.50 OHC/AdvOHV-6 Cylinder 2.0 115.7 0 0 0 1987 2.50 OHC/AdvOHV-8 Cylinder 2.0 132.3 0 0 0 1986 2.50 4-Valve/4-Cylinder 8.0 205.0 0 10 0 1988 4.25 4-Valve/6-Cylinder 8.0 280.0 0 15 0 1992 4.25 4 Valve/8-Cylinder 8.0 320.0 0 20 0 1994 4.25 5 Valve/6-Cylinder 8.0 300.0 0 18 0 1998 5.00 VVT-4 Cylinder 2.2 65.0 0 10 0 1994 1.25 VVT-6 Cylinder 2.2 141.0 0 20 0 1993 1.25 VVT-8 Cylinder 2.8 141.0 0 20 0 1993 1.25 VVL-4 Cylinder 2.8 198.0 0 25 0 1997 2.50 VVL-6 Cylinder 3.0 336.0 0 40 0 2000 2.50 VVL-8 Cylinder 3.4 395.0 0 50 0 2000 2.50 Camless Valve Actuation-4cyl 13.6 400.9 0 35 0 2020 3.25 Camless Valve Actuation-6cyl 13.6 561.3 0 55 0 2020 3.25 Camless Valve Actuation-8cyl 13.6 721.6 0 75 0 2020 3.25 Cylinder Deactivation 5.3 152.3 0 10 0 2004 0 Turbocharging/Supercharging 6.3 324.7 0 -100 0 1980 3.75 Engine Friction Reduction I 2.3 54.0 0 0 0 1992 0.75 Engine Friction Reduction II 2.8 60.9 0 0 0 2000 1.25 Engine Friction Reduction III 4.0 138.7 0 0 0 2008 1.75 Engine Friction Reduction IV 6.5 177.0 0 0 0 2016 2.25 Stoichiometric GDI/4-Cylinder 2.3 198.0 0 20 0 2006 2.50 Stoichiometric GDI/6-Cylinder 2.3 198.0 0 30 0 2006 2.50 Lean Burn GDI 10.0 640.5 0 20 0 2020 0 5W-30 Engine Oil 2.0 16.7 0 0 0 2003 0 5W-20 Engine Oil 3.1 150.0 0 0 0 2030 0 Electric Power Steering 2.0 107.0 0 0 0 2004 0 Improved Alternator 0.3 15.0 0 0 0 2005 0 Improved Oil/Water Pump 0.5 10.0 0 0 0 2000 0 Electric Oil/Water Pump 1.5 93.4 0 0 0 2007 0 Tires II 1.8 15.8 0 -8 0 1995 0 Tires III 2.7 19.9 0 -12 0 2005 0 Tires IV 3.8 22.9 0 -16 0 2015 0 Front Wheel Drive 6.0 250.0 0 0 -6.0 1980 0 Four Wheel Drive Improvements 1.3 93.8 0 0 -1.0 2000 0 42V-Launch Assist and Regenerative Breaking 7.5 280.0 0 80 0 2005 -2.50 42V-Engine Off at Idle 6.8 496.6 0 45 0 2005 0 Variable Compression Ratio 4.0 350.0 0 25 0 2015 0 1
Fractional changes refer to the percentage change from the base technology.
Sources: U.S. Energy Information Administration, Energy and Environment Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright 2002). National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S. Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).
70 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Table 7.2. Standard technology matrix for light trucks1 Per Unit Absolute Incremen-Fuel Incremen- Incremen- Incremen- tal Weight Efficiency tal Cost tal Cost tal Weight (Lbs./ Introduc- Horse power Change % (2000$) ($/UnitWt.) (Lbs.) UnitWt.) tion Year Change %
Unit Body Construction 4.0 100.0 0 0 -6.0 1980 0 Material Substitution II 3.3 0 0.4 0 -5.0 1994 0 Material Substitution III 6.6 0 0.6 0 -10.0 2002 0 Material Substitution IV 9.9 0 0.9 0 -15.0 2010 0 Material Substitution V 13.2 0 1.2 0 -20.0 2018 0 Drag Reduction II 2.0 32.0 0 0 0.0 1992 0 Drag Reduction III 4.1 57.0 0 0 0.2 1998 0 Drag Reduction IV 6.4 89.0 0 0 0.5 2006 0 Drag Reduction V 7.8 109.0 0 0 1.0 2014 0 Adv Low Loss Torque Converter 2.0 25.0 0 0 0 2005 0 Early Torque Converter Lockup 0.5 25.6 0 0 0 2003 0 Aggressive Shift Logic 1.5 30.5 0 0 0 1999 0 4-Speed Automatic 4.5 285.0 0 10 0 1980 0 5-Speed Automatic 2.5 90.0 0 20 0 1995 0 6-Speed Automatic 5.5 272.0 0 30 0 2003 0 6-Speed Manual 0.5 91.4 0 20 0 1995 0 CVT 5.0 222.0 0 -25 0 1998 0 Automated Manual Trans 3.4 157.5 0 0 0 2004 0 Roller Cam 2.0 16.0 0 0 0 1985 0 OHC/AdvOHV-4 Cylinder 2.0 99.0 0 0 0 1980 2.50 OHC/AdvOHV-6 Cylinder 2.0 115.7 0 0 0 1990 2.50 OHC/AdvOHV-8 Cylinder 2.0 132.3 0 0 0 1990 2.50 4-Valve/4-Cylinder 7.0 205.0 0 10 0 1998 4.25 4-Valve/6-Cylinder 7.0 280.0 0 15 0 2000 4.25 4 Valve/8-Cylinder 7.0 320.0 0 20 0 2000 4.25 5 Valve/6-Cylinder 7.0 300.0 0 18 0 2010 5.00 VVT-4 Cylinder 2.2 65.0 0 10 0 1998 1.25 VVT-6 Cylinder 2.2 141.0 0 20 0 1997 1.25 VVT-8 Cylinder 2.8 141.0 0 20 0 1997 1.25 VVL-4 Cylinder 2.8 198.0 0 25 0 2002 2.50 VVL-6 Cylinder 3.0 336.0 0 40 0 2001 2.50 VVL-8 Cylinder 3.4 395.0 0 50 0 2006 2.50 Camless Valve Actuation-4cyl 13.6 400.9 0 35 0 2020 3.25 Camless Valve Actuation-6cyl 13.6 561.3 0 55 0 2020 3.25 Camless Valve Actuation-8cyl 13.6 721.6 0 75 0 2020 3.25 Cylinder Deactivation 5.3 152.3 0 10 0 2004 0 Turbocharging/Supercharging 6.3 360.0 0 -100 0 1987 3.75 Engine Friction Reduction I 2.5 25.0 0 0 0 1992 0.75 Engine Friction Reduction II 3.5 63.0 0 0 0 2000 1.25 Engine Friction Reduction III 5.0 178.0 0 0 0 2010 1.75 Engine Friction Reduction IV 6.5 177.0 0 0 0 2016 2.25 Stoichiometric GDI/4-Cylinder 2.4 198.0 0 20 0 2008 2.50 Stoichiometric GDI/6-Cylinder 2.4 198.0 0 30 0 2010 2.50 Lean Burn GDI 10.8 640.5 0 20 0 2010 0 5W-30 Engine Oil 2.0 16.7 0 0 0 2003 0 5W-20 Engine Oil 3.1 150.0 0 0 0 2030 0 Electric Power Steering 1.5 90.2 0 0 0 2005 0 Improved Alternator 0.3 15.0 0 0 0 2005 0 Improved Oil/Water Pump 0.5 10.0 0 0 0 2000 0 Electric Oil/Water Pump 1.0 93.4 0 0 0 2008 0 Tires II 0.0 30.0 0 -8 0 1995 0 Tires III 1.3 15.4 0 -12 0 2005 0 Tires IV 2.7 19.5 0 -16 0 2015 0 Front Wheel Drive 2.0 250 0 0 -3.0 1984 0 Four Wheel Drive Improvements 1.3 93.8 0 0 -1.0 2000 0 42V-Launch Assist and Regenerative Breaking 7.5 280.0 0 80 0 2005 -2.50 42V-Engine Off at Idle 6.8 434.9 0 45 0 2005 0 Variable Compression Ratio 4.0 350.0 0 25 0 2015 0 1
Fractional changes refer to the percentage change from the base technology.
Sources: U.S. Energy Information Administration. Energy and Environment Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE)
Standards (Copyright 2002).
National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S.
Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 71
Transportation Demand Module Degradation factors are used to convert new vehicle tested fuel economy values to on-road fuel economy values (Table 7.3).
The degradation factors represent adjustments made to tested fuel economy values to account for the difference between fuel economy performance realized in the CAFE test procedure and fuel economy realized under normal driving conditions.
Table 7.3. Car and light truck degradation factors 2005 2010 2015 2020 2030 2035 Cars 79.8 81.8 82.2 82.2 82.2 82.2 Light Trucks 80.6 80.6 80.6 80.6 80.6 80.6 Source: U.S. Energy Information Administration, Transportation Sector Modules of the National Energy Modeling System, Model Documentation 2011, DOE/EIA-M070(2011), (Washington, DC, 2012).
! 66 $""4>"6"
The Transportation Demand Module divides commercial light-duty "eets into three types: business, government, and utility.
Based on this classi"cation, commercial light-duty "eet vehicles vary in survival rates and duration of in-"eet use before sale for use as personal vehicles (Table 7.4). The average length of time passenger cars are kept before being sold for personal use is 3 years for business use, 6 years for government use, and 5 years for utility use. Of total automobile sales to "eets in 2009, 75.1 percent are used in business "eets, 9.6 percent in government "eets, and 15.3 percent in utility "eets. Of total light truck sales to "eets in 2009, 47.3 percent are used in business "eets, 15.1 percent in government "eets, and 37.6 percent in utility "eets [3].
Both the automobile and light truck shares by "eet type are held constant from 2009 through 2035. In 2009, 18.2 percent of all automobiles sold and 16.9 percent of all light trucks sold were for "eet use. The share of total automobile and light truck sales slowly declines over the forecast period based on historic trends.
+- [ ' " &>" ""& $ -4>""4-4^
Mini Subcompact Compact Midsize Large 2-Seater Car Business 0.0 10.5 10.7 42.7 36.1 0.0 Government 0.0 2.8 40.0 2.8 54.4 0.0 Utility 0.0 7.9 34.7 12.3 45.1 0.0 SM Pk LG Pk SM Van LG Van SM Util LG Util Light Truck Business 7.9 35.1 7.9 26.8 5.5 16.8 Government 6.7 50.8 28.4 4.6 1.6 7.8 Utility 8.2 52.1 6.0 32.7 0.3 0.7 Source: U.S. Energy Information Administration, Archive--Alternative Transportation Fuels (ATF) and Alternative Fueled Vehicles (AFV), http://
www.eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use Alternative-fuel shares of "eet vehicle sales by "eet type are held constant at 2005 levels. Size class sales shares of vehicles are also held constant at 2005 levels (Table 7.5) [4]. Individual sales shares of new vehicles purchased by technology type are assumed to remain relatively constant for utility, government, and for business "eets using the previous 5-year average [5]
(Table 7.6).
Annual vehicle miles traveled (VMT) per vehicle by "eet type stays constant over the forecast period based on the Oak Ridge National Laboratory "eet data.
Fleet fuel economy for both conventional and alternative-fuel vehicles is assumed to be the same as the personal new vehicle fuel economy and is subdivided into six EPA size classes for cars and light trucks.
72 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module
+- [ ! 66 >"^ $-4>"$ "4
percentage Fleet Type by Size Class Automobiles Light Trucks Business Fleet Mini 3.1 2.5 Subcompact 23.4 8.4 Compact 26.6 23.3 Midsize 36.2 8.1 Large 9.9 14.2 2-seater 0.8 43.6 Government Fleet Mini 0.2 6.7 Subcompact 4.6 43.6 Compact 20.6 10.4 Midsize 28.6 17.1 Large 46.0 3.8 2-seater 0.0 18.4 Utility Fleet Mini 1.5 7.3 Subcompact 12.5 38.7 Compact 10.0 11.8 Midsize 59.2 18.9 Large 16.4 7.2 2-seater 0.4 16.1 Source: Oak Ridge National Laboratory, Fleet Characteristics and Data Issues, Stacy Davis and Lorena Truett, "nal report prepared for the Department of Energy, Energy Information Administration, Office of Energy Analysis, (Oak Ridge, Tn, January 2003).
+- [ P X$ &/$ $-4>""4"$ 4"4
percentage Technology Business Government Utility Cars Gasoline 99.10 72.78 95.52 Ethanol Flex 0.46 26.20 2.11 Electric 0.00 0.02 0.07 CNG Bi-Fuel 0.14 0.56 1.08 LPG Bi-Fuel 0.16 0.11 0.40 CNG 0.08 0.33 0.63 LPG 0.08 0.01 0.19 Light Trucks Gasoline 71.71 59.46 98.22 Ethanol Flex 16.29 35.09 0.49 Electric 0.04 0.07 0.05 CNG Bi-Fuel 1.28 2.29 0.51 LPG Bi-Fuel 7.93 2.55 0.31 CNG 1.54 0.49 0.24 LPG 1.22 0.05 0.18 Sources: U.S. Energy Information Administration, Archive-Alternative Transportation Fuels (ATF) and Alternative Fueled Vehicles (AFV), http://www.
eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 73
Transportation Demand Module The light commercial truck model The Light Commercial Truck Module of the NEMS Transportation Model represents light trucks that have a 8,501 to 10,000 pound gross vehicle weight rating (Class 2B vehicles). These vehicles are assumed to be used primarily for commercial purposes.
The module implements a twenty-"ve-year stock model that estimates vehicle stocks, travel, fuel economy, and energy use by vintage. Historic vehicle sales and stock data, which constitute the baseline from which the forecast is made, are taken from an Oak Ridge National Laboratory study [6]. The distribution of vehicles by vintage, and vehicle scrappage rates are derived from R.L. Polk & Co. registration data [7],[8]. Vehicle travel by vintage was constructed using vintage distribution curves and estimates of average annual travel by vehicle [9],[10].
The growth in light commercial truck VMT is a function of industrial output for agriculture, mining, construction, total manufacturing, utilities, and personal travel. These groupings were chosen for their correspondence with output measures being forecast by NEMS. The overall growth in VMT re"ects a weighted average based on the distribution of total light commercial truck VMT by sector. Forecasted fuel efficiencies are assumed to increase at the same annual growth rate as conventional gasoline light-duty trucks (<8,500 pounds gross vehicle weight).
Consumer vehicle choice assumptions The Consumer Vehicle Choice Module (CVCM) utilizes a nested multinomial logit (NMNL) model that predicts sales shares based on relevant vehicle and fuel attributes. The nesting structure "rst predicts the probability of fuel choice for multi-fuel vehicles within a technology set. The second level nesting predicts penetration among similar technologies within a technology set (i.e., gasoline versus diesel hybrids). The third level choice determines market share among the different technology sets [11].
The technology sets include:
t Conventional fuel capable (gasoline, diesel, compressed natural gas (CNG) and lique"ed petroleum gas (LNG), and "ex-fuel),
t Hybrid (gasoline and diesel),
t Plug-in hybrid (10 mile all-electric range and 40 mile all-electric range) t Dedicated alternative fuel (CNG and LPG),
t Fuel cell (gasoline, methanol, and hydrogen), and t Electric battery powered (100 mile range and 200 mile range) [12]
The vehicle attributes considered in the choice algorithm include: vehicle price, maintenance cost, battery replacement cost, range, multi-fuel capability, home refueling capability, fuel economy, acceleration and luggage space. With the exceptions of maintenance cost, battery replacement cost, and luggage space, vehicle attributes are determined endogenously [13]. Battery costs for plug-in hybrid electric and all-electric vehicles are based on a production based function over several technology phase periods. The fuel attributes used in market share estimation include availability and price. Vehicle attributes vary by six EPA size classes for cars and light trucks and fuel availability varies by Census division. The NMNL model coefficients were developed to re"ect purchase decisions for cars and light trucks separately.
Where applicable, CVCM fuel efficient technology attributes are calculated relative to conventional gasoline miles per gallon.
It is assumed that many fuel efficiency improvements in conventional vehicles will be transferred to alternative-fuel vehicles.
Speci"c individual alternative-fuel technological improvements are also dependent upon the CVCM technology type, cost, research and development, and availability over time. Make and model availability estimates are assumed according to a logistic curve based on the initial technology introduction date and current offerings. Coefficients summarizing consumer valuation of vehicle attributes were derived from assumed economic valuation compared to vehicle price elasticities. Initial CVCM vehicle stocks are set according to the EIA survey EIA-886 [14]. A fuel switching algorithm based on the relative fuel prices for alternative fuels compared to gasoline is used to determine the percentage of total VMT represented by alternative fuels in bi-fuel and "ex-fuel alcohol vehicles.
Freight truck assumptions The freight truck module estimates vehicle stocks, travel, fuel efficiency, and energy use for three size classes of trucks: light-medium (Class 3), heavy-medium (Classes 4-6), and heavy (Classes 7-8). The three size classes are further broken down into 13 subclasses for fuel economy classi"cation purposes (Table 7.7). These subclasses include two breakouts for light-medium size class, including pickup/van and vocational, one breakout for heavy-medium, including vocational, and ten breakouts for heavy.
The ten subclasses for heavy include parceling the class into class 7 or class 8, day cab or sleeper cab, and low, mid or high roof.
Within the size classes, the stock model structure is designed to cover 34 vehicle vintages and to estimate energy use by four fuel types: diesel, gasoline, LPG, and CNG. Fuel consumption estimates are reported regionally (by Census Division) according to the distillate fuel shares from the State Energy Data System [15]. The technology input data speci"c to the different types of trucks including the year of introduction, incremental fuel efficiency improvement, and capital cost of introducing the new technologies, are shown in Table 7.8.
74 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Table 7.7. Vehicle technology category for technology matrix for freight trucks Vehicle category Class Type Roof1 1 3 Pickup and Van -
2 3 Vocational -
3 4-6 Vocational -
4 7-8 Vocational -
5 7 Tractor - day cab low 6 7 Tractor - day cab mid 7 7 Tractor - day cab high 8 8 Tractor - day cab low 9 8 Tractor - day cab mid 10 8 Tractor - day cab high 11 8 Tractor - sleeper cab low 12 8 Tractor - sleeper cab mid 13 8 Tractor - sleeper cab high 1
Applies to Class 7 and 8 day and sleeper cabs only.
Table 7.8. Standard technology matrix for freight trucks Incremental Fuel Economy Vehicle Introduction Capital Costs Improvement Technology Type Category Year (2009$) (%)
Aerodynamics I: streamlined bumper, grill, windshield, roof 1 2010 58 1.5 Aerodynamics I: conventional features; general aerodynamic shape, removal of classic non-aerodynamic features 5.8 1995 1000 4.1 Aerodynamics I 7,10 1995 1000 4.6 Aerodynamics I 11 1995 1000 4.1 Aerodynamics I 13 1995 1000 4.6 Aerodynamics II: SmartWay features; streamlined shape, bumper grill, hood, mirrors, side fuel tank and roof fairings, side gap extenders 5.8 2004 1126 1.5 Aerodynamics II 7,10 2004 1126 3.1 Aerodynamics II 11 2004 1155 4.2 Aerodynamics II 13 2004 1506 4.2 Aerodynamics III: underbody air"ow, down exhaust, lowered ride height 7 2014 2303 4.2 Aerodynamics III 13 2014 2675 5.8 Aerodynamics IV: skirts, boat tails, nose cone, vortex stabilizer, pneumatic blowing 5-13 1995 5500 13.0 Tires I: low rolling resistance 1 2010 7 1.5 Tires I 2,3 2010 162 2.6 Tires I 4 2010 194 2.0 Tires I 5-7 2010 130 2.0 Tires I 8-13 2010 194 2.0 Tires II: super singles 5-10 2000 150 5.3 Tires II 11-13 2000 150 5.3 Tires III: single wide tires on trailer 5-13 2000 800 3.1 Weight Reduction I 1 2010 127 1.6 Weight Reduction I: aluminum dual tires or super singles 5-13 2010 650 1.0 Weight Reduction II: weight reduction 15% 3-13 2018 6200 3.0 Weight Reduction III: weight reduction 20% 3-13 2022 11000 3.5 Accessories I: Electric/electrohydraulic improvements; electric power steering or electrohydraulic power steering 1 2010 115 1.5 Accessories II: Improved accessories; electri"ed water, oil, fuel injection, power steering pump, aircompressor 1 2010 93 1.5 Accessories III: Auxiliary Power Unit 11-13 2000 5400 5.8 Transmission I: 8-speed Automatic from 6-speed automatic 1 2000 280 1.7 Transmission II: 6-Manual from 4-speed automatic 1 1995 150 1.0 Transmission III: Automated Manual Transmission 2-13 2000 5000 3.5 Diesel Engine I: aftertreatment improvements 1 2010 119 4.0 Diesel Engine I 2 2010 117 2.6 Diesel Engine II: low friction lubricants 1-13 2005 4 0.5 Diesel Engine III: variable valve actuation 2 2010 0 1.0 Diesel Engine III 3-13 2005 300 1.0 Diesel Engine IV: engine friction reduction, low tension piston rings, roller cam followers, piston skirt design, improved crankshaft design and bearings; coating 1-2 2010 116 1.0 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 75
Transportation Demand Module Table 7.8. Standard technology matrix for freight trucks (cont.)
Incremental Fuel Economy Vehicle Introduction Capital Costs Improvement Technology Type Category Year (2009$) (%)
Diesel Engine IV: engine friction reduction, improved bearings to allow lower viscosity oil 3-4 2010 250 1.0 Diesel Engine IV 5-13 2010 250 1.0 Diesel Engine V: improved turbo efficiency 2 2010 18 1.5 Diesel Engine V 3 2010 18 1.5 Diesel Engine V 5-7 2010 18 1.5 Diesel Engine V 4 2010 18 1.5 Diesel Engine V 8-13 2010 18 1.5 Diesel Engine VI: improved water, oil, fuel pump; pistons; valve train friction reduction 2 2010 213 1.3 Diesel Engine VI 3 2010 186 1.3 Diesel Engine VI 5-7 2010 186 1.3 Diesel Engine VI: improved water, oil, and fuel pump; pistons 4 2010 150 1.3 Diesel Engine VI 8-13 2010 150 1.3 Diesel Engine VII: improved cylinder head, fuel rail and injector, EGR cooler 2 2010 42 4.7 Diesel Engine VII 3 2010 31 4.7 Diesel Engine VII 5-7 2010 31 4.7 Diesel Engine VII 4 2010 31 4.7 Diesel Engine VII 8-13 2010 31 4.7 Diesel Engine VIII: turbo mechanical compounding 5-7 2017 1000 3.9 Diesel Engine VIII 8-13 2017 1000 3.9 Diesel Engine IX: low temperature EGR, improved turbochargers 1 2010 184 5.0 Diesel Engine X: sequential downsizing/turbocharging 5-13 2010 1200 2.5 Diesel Engine XI: waste heat recovery, Organic Rankine Cycle (bottoming cycle) 3-13 2019 10000 8.0 Diesel Engine XII: electric turbo compounding 4-13 2020 8000 7.6 Gasoline Engine I: low friction lubricants 1-13 2010 4 0.5 Gasoline Engine II: coupled cam phasing 2-4 2010 46 2.6 Gasoline Engine III: engine friction reduction; low tension piston rings, roller cam followers, piston skirt design, improved crankshaft design and bearings; coating 1 2010 116 2.0 Gasoline III 2 2010 116 2.0 Gasoline III 3-4 2010 95 2.0 Gasoline Engine IV: stoichiometric gasoline direct injection V8 1-2 2006 481 1.5 Gasoline Engine IV 3-4 2014 450 1.5 Gasoline Engine V: turbocharging and downsizing SGDI V8 to V6 1-4 2006 1743 2.1 Gasoline Engine VI: lean burn GDI 1-4 2020 750 13.0 Gasoline Engine VII: HCCI 1-4 2030 685 12.0 Hybrid System I: 42V engine off at idle 1-2 2005 1500 7.0 Hybrid System I 3-4 2005 1500 4.5 Hybrid System II: dual mode hybrid 1-2 2008 12000 25.0 Hybrid System II: electric, ePTO, or hydraulic 3-4 2009 26667 30.0 Hybrid System II: 4 kWh battery, 50 kW motor generator 5-13 2012 26000 5.5 Source: Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol. 76, No. 179, (September 2011). Final Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, Regulatory Impact Analysis, U.S. Environmental Protection Agency and U.S. Department of Transportation, (August 2011). Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and CO2 Emissions, Final Report, TIAX, LLC. (October 2009). Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle Fuel Economy, Final Report, ICF International, Prepared for the U.S. Energy Information Administration, (August 2010). Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Research Council of the National Academy of Sciences, (2010).
The freight module uses projections of industrial output to estimate growth in freight truck travel. The industrial output is converted to an equivalent measure of volume output using freight adjustment coefficients [16],[17]. These freight adjustment coefficients vary by North American Industry Classi"cation System (NAICS) code with the deviation diminishing gradually over time toward parity. Freight truck load-factors (ton-miles per truck) by NAICS code are constants formulated from historical data [18].
Fuel economy of new freight trucks is dependent on the market penetration of advanced technology components [19]. For the advanced technology components, market penetration is determined as a function of technology type, cost effectiveness, and introduction year. Cost effectiveness is calculated as a function of fuel price, vehicle travel, fuel economy improvement, and incremental capital cost.
76 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Heavy truck freight travel is estimated by class size and fuel type based on matching projected freight travel demand (measured by industrial output) to the travel supplied by the current "eet. Travel by vintage and size class is then adjusted so that total travel meets total demand.
Initial heavy vehicle travel, by vintage and size class, is derived by the U.S. Energy Information Administration using Vehicle Inventory and Use Survey (VIUS) data [20]. Initial freight truck stocks by vintage are obtained from R. L. Polk & Co. and are distributed by fuel type using VIUS data. Vehicle scrappage rates are also estimated by the U.S. Energy Information Administration using R. L. Polk & Co. data.
Freight rail assumptions The freight rail module uses the industrial output by NAICS code measured in real 1987 dollars and converts these dollars into an adjusted volume equivalent. Coal production from the NEMS Coal Market Module is used to adjust coal-based rail travel. Freight rail adjustment coefficients (used to convert dollars to volume equivalents) are based on historical data and remain constant
[21],[22]. Initial freight rail efficiencies are based on historic data taken from the Transportation Energy Data Book [23]. The distribution of rail fuel consumption by fuel type is also based on historical data and remains constant over the projection [24].
Regional freight rail consumption estimates are distributed according to the State Energy Data System [25].
Domestic and international shipping assumptions Similar to the previous sub-module, the domestic freight shipping module uses the industrial output by NAICS code measured in real 1987 dollars and converts these dollars into an adjusted volume equivalent.
The freight adjustment coefficients (used to convert dollars to volume equivalents) are based on historical data. Domestic shipping efficiencies are based on the model developed by Argonne National Laboratory. The energy consumption in the international shipping module is a function of the total level of imports and exports. The distribution of domestic and international shipping fuel consumption by fuel type is based on historical data and remains constant throughout the forecast [26]. Regional domestic shipping consumption estimates are distributed according to the residual oil regional shares in the State Energy Data System [27].
The air model The air model is a thirteen region world demand and supply model (Table 7.9). For each region, demand is computed for domestic travel (both takeoff and landing occur in the same region) and international travel (either takeoff or landing is in the region but not both). Once the demand for aircraft is determined, the stock efficiency module moves aircraft between regions to satisfy the demand.
+- [ +$" & "$/ 6
Region Number Region Major Countries in Region 1 United States United States 2 Canada Canada 3 Central America Mexico 4 South America Brazil 5 Europe France, Germany 6 Africa S. Africa 7 Middle East Egypt 8 Russia Russia 9 China China 10 Northeast Asia Japan, Korea 11 Southeast Asia Vietnam 12 Southwest Asia India 13 Oceania Australia, New Zealand Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009)
Air travel demand assumptions The air travel demand module calculates the domestic and international per-capita revenue passenger miles (RPM-PC) for each region. Domestic and international revenue passenger miles are based on the historical data in Table 7.10, [28] per capita income for the United States, per-capita GDP for the non-U.S. regions, and ticket prices. The revenue ton miles of air freight for the United States are based on merchandise exports, gross domestic product, and fuel cost. For the non-U.S. regions, revenue ton miles are based on GDP growth in the region [29].
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 77
Transportation Demand Module Airport capacity constraints based on the Federal Aviation Administration (FAA) Airport Capacity Benchmark Report 2004 are incorporated into the air travel demand module using airport capacity measures. [30] Airport capacity is de"ned by the maximum number of "ights per hour airports can routinely handle, the amount of time airports operate at optimal capacity, and passenger load factors. Capacity expansion is expected to be delayed due to the economic environment and fuel costs.
Aircraft stock/efficiency assumptions The aircraft stock and efficiency module consists of a world regional stock model of wide body, narrow body, and regional jets by vintage. Total aircraft supply for a given year is based on the initial supply of aircraft for model year 2009, new passenger sales, and the survival rate by vintage (Table 7.11) [31]. New passenger sales are a function of revenue passenger miles and gross domestic product.
Wide and narrow body planes over 25 years of age are placed as cargo jets according to a cargo percentage varying from 50 percent of 25-year-old planes to 100 percent of those aircraft 30 years and older. The available seat-miles per plane, which measure the carrying capacity of the airplanes by aircraft type increase gradually over time. Domestic and international travel are combined into a single regional demand for seat-miles and passed to the Aircraft Fleet Efficiency Submodule, which adjusts the initial aircraft stock to meet that demand. For each region, starting with the United States, the initial stock is adjusted by moving aircraft between regions.
Technological availability, economic viability, and efficiency characteristics of new aircraft are assumed to grow at a "xed rate. Fuel efficiency of new aircraft acquisitions represents an improvement over the stock efficiency of surviving airplanes. A generic set of new technologies (Table 7.12) are introduced in different years and with a set of improved efficiencies over the base year (2007).
Regional shares of all types of aircraft fuel use are assumed to be constant and are consistent with the State Energy Data System estimate of regional jet fuel shares.
+- [ % " " 6""" 6"6 Population Region (million) GDP (2006$) GDP_PC United States 310.2 13,088 42,106.0 Canada 34.1 1,239 36,383.8 Central America 197.3 2,025 10,262.7 South Amercia 393.1 3,993 10,158.3 Europe 607.9 15,367 25,280.1 Africa 931.9 2,636 2,829.1 Middle East 298.7 3,083 10,318.7 Russia 278.6 2,843 10,203.4 China 1,347.3 9,577 7,108.2 Northeast Asia 200.6 5,024 25,045.1 Southeast Asia 627.9 3,752 5,975.7 Southwest Asia 1,629.3 4,971 3,015.2 Oceania 27.9 909 32,641.2 Region RPM (billion) RPM_PC (thousand)
Domestic United States 564.8 1,816.9 Canada 27.1 795.0 Central America 20.1 101.8 South America 70.7 179.9 Europe 399.4 657.0 Africa 31.0 33.2 Middle East 47.8 159.9 Russia 32.8 117.9 China 208.0 154.4 Northeast Asia 44.5 221.8 Southeast Asia 81.0 129.0 Southwest Asia 30.4 18.7 Oceania 50.0 1,795.2 78 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module
+- [ % " " 6""" 6"6V " W Population Region (million) GDP (2006$)
International United States 244.2 785.7 Canada 53.1 1,559.8 Central America 63.7 322.9 South America 49.8 126.7 Europe 378.3 622.4 Africa 59.2 63.5 Middle East 113.5 380.0 Russia 31.0 111.1 China 90.9 67.5 Northeast Asia 93.0 463.5 Southeast Asia 132.9 211.6 Southwest Asia 49.5 30.4 Oceania 44.0 1,579.9 Source: Global Insight 2006 chained weighted dollars, Boeing Current Market Outlook 2009.
+- [ % &" 4 Age of Aircraft (years)
Aircraft Type New 1-10 11-20 21-30 >30 Total Passenger Narrow Body United States 102 1456 1527 885 285 4255 Canada 5 144 82 18 14 263 Central America 12 173 68 110 101 464 South Amercia 42 279 143 180 148 792 Europe 204 1630 1013 224 32 3103 Africa 22 148 164 221 145 700 Middle East 60 215 164 61 50 550 Russia 15 202 413 362 284 1276 China 168 848 282 16 2 1316 Northeast Asia 24 149 111 7 5 296 Southeast Asia 83 239 212 164 38 736 Southwest Asia 27 224 47 49 8 355 Oceania 14 165 49 2 0 230 Wide Body United States 9 201 326 176 30 742 Canada 0 30 32 31 0 93 Central America 0 9 7 13 0 29 South America 3 43 43 9 4 102 Europe 36 345 382 74 16 853 Africa 2 57 43 43 15 160 Middle East 37 238 149 78 13 515 Russia 4 20 93 79 0 196 China 22 132 115 4 0 273 Northeast Asia 17 146 161 26 0 350 Southeast Asia 21 204 170 24 13 432 Southwest Asia 3 51 33 26 4 117 Oceania 7 56 57 8 0 128 Regional Jets United States 35 1774 581 65 15 2470 Canada 8 132 128 74 50 392 Central America 5 85 79 20 0 189 South America 32 94 118 33 5 282 Europe 84 671 721 132 0 1608 Africa 24 106 133 68 16 347 Middle East 15 86 91 11 4 207 Russia 1 73 80 76 4 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 79
Transportation Demand Module
+- [ % &" 4V " W Age of Aircraft (years)
Aircraft Type New 1-10 11-20 21-30 >30 Total China 18 112 15 2 0 147 Northeast Asia 8 56 5 0 0 69 Southeast Asia 18 0 101 52 11 261 Southwest Asia 7 0 29 8 3 100 Oceania 6 0 97 46 0 247 Wide Body United States 14 86 232 226 128 686 Canada 0 0 0 3 4 7 Central America 0 2 1 3 4 10 South America 0 8 2 7 7 24 Europe 5 32 54 59 12 162 Africa 0 0 2 1 2 5 Middle East 4 12 18 18 5 57 Russia 0 5 9 5 0 19 China 9 35 37 15 0 96 Northeast Asia 0 30 19 4 0 53 Southeast Asia 0 32 18 5 0 59 Southwest Asia 0 0 5 4 1 10 Oceania 0 0 0 0 0 0 Regional Jets United States 0 0 25 3 0 28 Canada 0 0 0 7 0 7 Central America 0 0 4 1 0 5 South America 0 0 0 6 0 6 Europe 0 4 59 44 0 107 Africa 0 0 0 6 1 7 Middle East 0 0 0 0 0 0 Russia 0 0 1 0 0 1 China 0 0 0 0 0 0 Northeast Asia 0 0 0 0 0 0 Southeast Asia 0 0 2 3 0 5 Southwest Asia 0 0 1 0 0 1 Oceania 0 0 1 3 0 4 Survival Curve (fraction) New 5 10 20 35 Narrow Body 1.000 0.9998 0.9992 0.9960 0.9200 Wide Body 1.000 0.9980 0.9954 0.9860 0.8500 Regional Jets 1.000 0.9967 0.9900 0.9400 0.8350 Source: Jet Information Services, 2009 World Jet Inventory (2009).
+- [ X""$ 46"=& "
Technology Introduction Year Fractional Efficiency Improvement Jet Fuel Trigger Price (1987$/per gallon)
Technology #1 2008 0.03 1.34 Technology #2 2014 0.07 1.34 Technology #3 2020 0.11 1.34 Technology #4 2025 0.15 1.34 Technology #5 2018 0.20 1.34 Technology #6 2018 0.00 1.34 Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009) 80 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Legislation and regulations Light Duty Vehicle Combined Corporate Average Fuel Economy (CAFE) Standards The AEO2012 Reference case includes both the attribute-based CAFE standards for LDVs for Model Year (MY) 2011 and the joint attribute-based CAFE and vehicle GHG emissions standards for MY 2012 to MY 2016. However, the Reference case assumes that LDV CAFE standards increase to 35 miles per gallon by MY 2020, as called for in the Energy Independence and Security Act of 2007 (EISA2007). CAFE standards are then held constant in subsequent model years, although the fuel economy of new LDVs continues to rise modestly over time.
Heavy Duty Vehicle Combined Corporate Average Fuel Economy Standards On September 15, 2011, the EPA and NHTSA jointly announced a "nal rule, called the HD National Program [32], which for the "rst time establishes greenhouse gas (GHG) emissions and fuel consumption standards for on-road heavy-duty trucks and their engines. The AEO2012 Reference case incorporates the new standards for heavy-duty vehicles (HDVs) with gross vehicle weight rating (GVWR) above 8,500 pounds (Classes 2b through 8). The HD National Program standards begin for MY 2014 vehicles and engines and are fully phased in by MY 2018. AEO2012 models standard compliance among 13 HDV regulatory classi"cations that represent the discrete vehicle categories set forth in the rule.
Energy Independence and Security Act of 2007 (EISA2007)
A fuel economy credit trading program is established based on EISA2007. Currently, CAFE credits earned by manufacturers can be banked for up to 3 years and can only be applied to the "eet (car or light truck) from which the credit was earned. Starting in model year 2011, the credit trading program will allow manufacturers whose automobiles exceed the minimum fuel economy standards to earn credits that can be sold to other manufacturers whose automobiles fail to achieve the prescribed standards.
The credit trading program is designed to ensure that the total oil savings associated with manufacturers that exceed the prescribed standards are preserved when credits are sold to manufacturers that fail to achieve the prescribed standards.
While the credit trading program begins in 2011, EISA2007 allows manufacturers to apply credits earned to any of the 3 model years prior to the model year the credits are earned, and to any of the 5 model years after the credits are earned. The transfer of credits within a manufacturers "eet is limited to speci"c maximums. For model years 2011 through 2013, the maximum transfer is 1.0 mpg; for model years 2014 through 2017, the maximum transfer is 1.5 mpg; and for model years 2018 and later, the maximum credit transfer is 2.0 mpg. NEMS currently allows for sensitivity analysis of CAFE credit banking by manufacturer "eet, but does not model the trading of credits across manufacturers. The AEO2012 does not consider trading of credits since this would require signi"cant modi"cations to the NEMS and detailed technology cost and efficiency data by manufacturer, which are not readily available.
The CAFE credits speci"ed under the Alternative Motor Fuels Act (AMFA) through 2019 are extended. Prior to passage of this Act, the CAFE credits under AMFA were scheduled to expire after model year 2010. Currently, 1.2 mpg is the maximum CAFE credit that can be earned from selling alternative fueled vehicles. EISA2007 extends the 1.2 mpg credit maximum through 2014 and reduces the maximum by 0.2 mpg for each following year until it is phased out by model year 2020. NEMS does model CAFE credits earned from alternative fuel vehicles sales.
American Recovery and Reinvestment Act of 2009 and Energy Improvement and Extension Act of 2008 ARRA Title I, Section 1141, modi"ed the EIEA2008 Title II, Section 205, tax credit for the purchase of new, quali"ed plug-in electric drive motor vehicles. According to the legislation, a quali"ed plug-in electric drive motor vehicle must draw propulsion from a traction battery with at least 4 kilowatthours of capacity and be propelled to a signi"cant extent by an electric motor which draws electricity from a battery that is capable of being recharged from an external source of electricity.
The tax credit for the purchase of a plug-in electric vehicle is $2,500, plus, starting at a battery capacity of 5 kilowatthours, an additional $417 per kilowatthour battery credit up to a maximum of $7,500 per vehicle. The tax credit eligibility and phase-out are speci"c to an individual vehicle manufacturer. The credits are phased out once a manufacturers cumulative sales of quali"ed vehicles reach 200,000. The phaseout period begins two calendar quarters after the "rst date in which a manufacturers sales reach the cumulative sales maximum after December 31, 2009. The credit is reduced to 50 percent of the total value for the "rst two calendar quarters of the phase-out period and then to 25 percent for the third and fourth calendar quarters before being phased out entirely thereafter. The credit applies to vehicles with a gross vehicle weight rating of less than 14,000 pounds.
ARRA also allows a tax credit of 10 percent against the cost of a quali"ed electric vehicle with a battery capacity of at least 4 kilowatthours subject to the same phase out rules as above. The tax credits for quali"ed plug-in electric drive motor vehicles and electric vehicles are included in AEO2012.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 81
Transportation Demand Module Energy Policy Act of 1992 (EPACT)
Fleet alternative-fuel vehicle sales necessary to meet the EPACT regulations are derived based on the mandates as they currently stand and the Commercial Fleet Vehicle Module calculations. Total projected AFV sales are divided into "eets by government, business, and fuel providers (Table 7.13).
Because the commercial "eet model operates on three "eet type representations (business, government, and utility), the federal and state mandates are weighted by "eet vehicle stocks to create a composite mandate for both. The same combining methodology is used to create a composite mandate for electric utilities and fuel providers based on "eet vehicle stocks [33].
+- [ 5!+ "6"& 5j$-4>""44
percent Year Federal State Fuel Providers Electric Utilities 2005 75 75 70 90 Source: U.S. Energy Information Administraiton, Energy Efficiency and Renewable Energy (Washington, DC, 2005), www1.eere.energy.gov/vehicles and fuels/epact/state/statutes_regulations.,html.
Low Emission Vehicle Program (LEVP)
The LEVP was originally passed into legislation in 1990 in the State of California. It began as the implementation of a voluntary opt-in pilot program under the purview of Clean Air Act Amendments of 1990 (CAAA90), which included a provision that other States could opt in to the California program to achieve lower emissions levels than would otherwise be achieved through CAAA90. Fourteen states have elected to adopt the California LEVP.
The LEVP is an emissions-based policy, setting sales mandates for 6 categories of low-emission vehicles: low-emission vehicles (LEVs), ultra-low-emission vehicles (ULEVs), super-ultra low emission vehicles (SULEVs), partial zero-emission vehicles (PZEVs), advanced technology partial zero emission vehicles (AT-PZEVs), and zero-emission vehicles (ZEVs). The LEVP requires that in 2005, 10 percent of a manufacturers sales are ZEVs or equivalent ZEV earned credits, increasing to 11 percent in 2009, 12 percent in 2012, 14 percent in 2015, and 16 percent in 2018 where it remains constant thereafter. In August 2004, CARB enacted further amendments to the LEVP that place a greater emphasis on emissions reductions from PZEVs and AT-PZEVs and requires that manufacturers produce a minimum number of fuel cell and electric vehicles. In addition, manufacturers are allowed to adopt alternative compliance requirements for ZEV sales that are based on cumulative fuel cell vehicle sales targets for vehicles sold in all States participating in Californias LEVP. Under the alternative compliance requirements, ZEV credits can also be earned by selling battery electric vehicles. Currently, all manufacturers have opted to adhere to the alternative compliance requirements.
The mandate still includes phase-in multipliers for pure ZEVs and allows 20 percent of the sales requirement to be met with AT-PZEVs and 60 percent of the requirement to be met with PZEVs. AT-PZEVs and PZEVs are allowed 0.2 credits per vehicle.
EIA assumes that credit allowances for PZEVs will be met with conventional vehicle technology, hybrid vehicles will be sold to meet the AT-PZEV allowances, and that hydrogen fuel cell vehicles will be sold to meet the pure ZEV requirements under the alternative compliance path.
+ "" ""
Integrated High Technology case In the Integratged High Technology case for cars and light trucks, the conventional fuel saving technology characteristics are based on NHTSA and EPA values [34]. Tables 7.14 and 7.15, summarize the high technology matrices for cars and light trucks.
Table 7.16 re"ects the high technology case assumptions for freight trucks. These re"ect optimistic values, with respect to effi-ciency improvement and capital cost, for advanced technologies [35-38]. For the air module, the Integrated High Technology case re"ects earlier introduction years for the new aircraft technologies and a greater penetration share, Table 7.17.
82 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Table 7.14. High technology matrix for cars Incremental Per Unit Fuel Absolute Incremental Efficiency Incremental Incremental Incremental Weight Introduc- Horse-power Change Cost Cost Weight (Lbs./Unit tion Change
(%) (1990$) ($/Unit Wt.) (Lbs.) Wt.) Year (%)
Unit Body Construction 4.0 100.0 0 0 -6.0 1980 0 Material Substitution II 3.3 0 0.4 0 -5.0 1990 0 Material Substitution III 6.6 0 0.6 0 -10.0 1998 0 Material Substitution IV 9.9 0 0.9 0 -15.6 2006 0 Material Substitution V 13.2 0 1.2 0 -20.0 2014 0 Drag Reduction II 1.6 16.0 0 0 0 1988 0 Drag Reduction III 3.2 32.0 0 0 0.2 1992 0 Drag Reduction IV 6.3 45.0 0 0 0.5 2000 0 Drag Reduction V 8.0 53.5 0 0 1.0 2010 0 Adv Low Loss Torque Converter 2.0 25.0 0 0 0 1999 0 Early Torque Converter Lockup 1.0 25.6 0 0 0 2002 0 Aggressive Shift Logic 2.0 30.5 0 0 0 1999 0 4-Speed Automatic 4.5 285.0 0 10 0 1980 0 5-Speed Automatic 8.0 106.5 0 20 0 1995 0 6-Speed Automatic 5.5 170.0 0 30 0 2003 0 6-Speed Manual 2.0 91.4 0 20 0 1995 0 CVT 8.0 240.5 0 -25 0 1998 0 Automated Manual Trans 12.0 120.4 0 0 0 2004 0 Roller Cam 2.0 16.0 0 0 0 1980 0 OHC/AdvOHV-4 Cylinder 3.0 93.1 0 0 0 1980 2.50 OHC/AdvOHV-6 Cylinder 3.0 108.9 0 0 0 1987 2.50 OHC/AdvOHV-8 Cylinder 3.0 124.7 0 0 0 1986 2.50 4-Valve/4-Cylinder 8.8 205.0 0 10 0 1988 4.25 4-Valve/6-Cylinder 8.8 280.0 0 15 0 1992 4.25 4 Valve/8-Cylinder 8.8 320.0 0 20 0 1994 4.25 5 Valve/6-Cylinder 9.0 300.0 0 18 0 1998 5.00 VVT-4 Cylinder 3.0 35.0 0 10 0 1994 1.25 VVT-6 Cylinder 3.0 87.5 0 20 0 1993 1.25 VVT-8 Cylinder 3.0 90.0 0 20 0 1993 1.25 VVL-4 Cylinder 3.0 144.3 0 25 0 1997 2.50 VVL-6 Cylinder 3.0 220.0 0 40 0 2000 2.50 VVL-8 Cylinder 3.0 285.0 0 50 0 2000 2.50 Camless Valve Actuation-4cyl 15.1 363.8 0 35 0 2020 3.25 Camless Valve Actuation-6cyl 15.1 513.0 0 55 0 2020 3.25 Camless Valve Actuation-8cyl 15.1 675.5 0 75 0 2020 3.25 Cylinder Deactivation 7.5 60.1 0 10 0 2004 0 Turbocharging/ Supercharging 7.5 324.7 0 -100 0 1980 3.75 Engine Friction Reduction I 2.3 54.0 0 0 0 1992 0.75 Engine Friction Reduction II 3.5 60.9 0 0 0 2000 1.75 Engine Friction Reduction III 5.0 52.1 0 0 0 2008 1.75 Engine Friction Reduction IV 6.5 177.0 0 0 0 2016 2.25 Stoichiometric GDI/4-Cylinder 2.9 198.0 0 20 0 2006 2.50 Stoichiometric GDI/6-Cylinder 2.9 198.0 0 30 0 2006 2.50 Lean Burn GDI 10.0 640.5 0 20 0 2020 0 5W-20 Engine Oil 2.0 16.7 0 0 0 2003 0 OW-20 Engine Oil 3.1 150.0 0 0 0 2030 0 Electric Power Steering 2.0 84.2 0 0 0 2004 0 Improved Alternator 0.3 15.0 0 0 0 2005 0 Improved Oil/Water Pump 0.5 10.0 0 0 0 2000 0 Electric Oil/Water Pump 1.5 93.4 0 0 0 2007 0 Tires II 2.0 6.1 0 -8 0 1995 0 Tires III 3.5 12.3 0 -12 0 2005 0 Tires IV 5.0 16.9 0 -16 0 2015 0 Front Wheel Drive 6.0 250.0 0 0 -6.0 1980 0 Four Wheel Drive Improvements 2.0 93.8 0 0 -1.0 2000 0 42V-Launch Assist and Regenerative Breaking 7.5 280.0 0 80 0 2005 -2.50 42V-Engine Off at Idle 7.5 496.6 0 45 0 2005 0 Variable Compression Ratio 4.0 350.0 0 25 0 2015 0 Source: Energy and Environmental Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright 2002).
National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S.
Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005)
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 83
Transportation Demand Module
+- [ \$"$ 46"=& $""@
Per Unit Fuel Absolute Incremental Horse-Efficiency Incremental Incremental Incremental Weight Introduc- power Change Cost Cost Weight (Lbs./Unit tion Change
(%) (2000$) ($/Unit Wt.) (Lbs.) Wt.) Year (%)
Unit Body Construction 4.0 100.0 0 0 -6.0 1980 0 Material Substitution II 3.3 0 0.4 0 -5.0 1994 0 Material Substitution III 6.6 0 0.6 0 -10.0 2002 0 Material Substitution IV 9.9 0 0.9 0 -15.0 2010 0 Material Substitution V 13.2 0 1.2 0 -20.0 2018 0 Drag Reduction II 2.3 32.0 0 0 0 1992 0 Drag Reduction III 4.1 57.0 0 0 0.2 1998 0 Drag Reduction IV 6.4 89.0 0 0 0.5 2006 0 Drag Reduction V 7.8 109.0 0 0 1.0 2014 0 Adv Low Loss Torque Converter 2.0 25.0 0 0 0 2005 0 Early Torque Converter Lockup 0.5 25.6 0 0 0 2003 0 Aggressive Shift Logic 2.0 30.5 0 0 0 1999 0 4-Speed Automatic 4.5 285.0 0 10 0 1980 0 5-Speed Automatic 8.0 106.5 0 20 0 1995 0 6-Speed Automatic 5.5 259.0 0 30 0 2003 0 6-Speed Manual 2.0 91.4 0 20 0 1995 0 CVT 8.0 130.0 0 -25 0 1998 0 Automated Manual Trans 3.4 120.4 0 0 0 2004 0 Roller Cam 2.0 16.0 0 0 0 1985 0 OHC/AdvOHV-4 Cylinder 3.5 93.1 0 0 0 1980 2.50 OHC/AdvOHV-6 Cylinder 3.5 108.9 0 0 0 1990 2.50 OHC/AdvOHV-8 Cylinder 3.5 124.7 0 0 0 1990 2.50 4-Valve/4-Cylinder 7.0 205.0 0 10 0 1998 4.25 4-Valve/6-Cylinder 7.0 280.0 0 15 0 2000 4.25 4 Valve/8-Cylinder 7.0 320.0 0 20 0 2000 4.25 5 Valve/6-Cylinder 7.0 300.0 0 18 0 2010 5.00 VVT-4 Cylinder 3.0 48.9 0 10 0 1998 1.25 VVT-6 Cylinder 3.0 97.8 0 20 0 1997 1.25 VVT-8 Cylinder 3.0 97.8 0 20 0 1997 1.25 VVL-4 Cylinder 3.0 144.3 0 25 0 2002 2.50 VVL-6 Cylinder 3.0 220.0 0 40 0 2001 2.50 VVL-8 Cylinder 3.0 285.0 0 50 0 2006 2.50 Camless Valve Actuation-4cyl 15.1 363.8 0 35 0 2020 3.25 Camless Valve Actuation-6cyl 15.1 513.0 0 55 0 2020 3.25 Camless Valve Actuation-8cyll 15.1 657.5 0 75 0 2020 3.25 Cylinder Deactivation 7.5 60.1 0 10 0 2004 0 Turbocharging/Supercharging 7.5 339.0 0 -100 0 1987 3.75 Engine Friction Reduction I 2.5 25.0 0 0 0 1992 0.75 Engine Friction Reduction II 3.5 31.2 0 0 0 2000 1.25 Engine Friction Reduction III 5.0 62.5 0 0 0 2010 1.75 Engine Friction Reduction IV 6.5 67.5 0 0 0 2016 2.75 Stoichiometric GDI/4-Cylinder 2.9 198.0 0 20 0 2008 2.50 Stoichiometric GDI/6-Cylinder 2.9 198.0 0 30 0 2010 2.50 Lean Burn GDI 11.5 640.5 0 20 0 2010 0 5W-20 Engine Oil 2.0 16.7 0 0 0 2003 0 OW-20 Engine Oil 3.1 150.0 0 0 0 2030 0 Electric Power Steering 2.0 84.2 0 0 0 2005 0 Improved Alternator 0.3 15.0 0 0 0 2005 0 Improved Oil/Water Pump 0.5 10.0 0 0 0 2000 0 Electric Oil/Water Pump 1.0 93.4 0 0 0 2008 0 Tires II 2.0 30.0 0 -8 0 1995 0 Tires III 3.5 5.6 0 -12 0 2005 0 Tires IV 5.0 11.8 0 -16 0 2015 0 Front Wheel Drive 6.0 250.0 0 0 -3.0 1984 0 Four Wheel Drive Improvements 2.0 93.8 0 0 -1.0 2000 0 42V-Launch Assist and Regenerative Breaking 7.5 280.0 0 80 0 2005 -2.50 42V-Engine Off at Idle 7.5 434.9 0 45 0 2005 0 Variable Compression Ratio 4.0 350.0 0 25 0 2015 0 Source: Energy and Environmental Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright 2002).
National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S.
Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).
84 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Table 7.16. High technology matrix for freight trucks Incremental Fuel Capital Economy Vehicle Costs Improvement Technology Type Category (2009$) (%)
Aerodynamics I: streamlined bumper, grill, windshield, roof 1 53 2.0 Aerodynamics I: conventional features; general aerodynamic shape, removal of classic non-aerodynamic features 5.8 900 4.5 Aerodynamics I 7,10 900 5.1 Aerodynamics I 11 900 4.5 Aerodynamics I 13 900 5.1 Aerodynamics II: SmartWay features; streamlined shape, bumper grill, hood, mirrors, side fuel tank and roof fairings, side gap extenders 5.8 997 2.0 Aerodynamics II 7,10 997 4.0 Aerodynamics II 11 1040 5.0 Aerodynamics II 13 1355 5.0 Aerodynamics III: underbody air"ow, down exhaust, lowered ride height 7 1552 5.0 Aerodynamics III 13 1803 7.0 Aerodynamics IV: skirts, boat tails, nose cone, vortex stabilizer, pneumatic blowing 5-13 4950 14.0 Tires I: low rolling resistance 1 6 2.0 Tires I 2,3 110 3.0 Tires I 4 131 2.2 Tires I 5-7 114 2.2 Tires I 8-13 172 2.2 Tires II: super singles 5-10 140 6.2 Tires II 11-13 140 6.2 Tires III: single wide tires on trailer 5-13 720 3.4 Weight Reduction I 1 116 1.8 Weight Reduction I: aluminum dual tires or super singles 5-13 580 1.1 Weight Reduction II: weight reduction 15% 3-13 5580 3.3 Weight Reduction III: weight reduction 20% 3-13 9900 3.9 Accessories I: Electric/electrohydraulic improvements; electric power steering or electrohydraulic power steering 1 105 2.0 Accessories II: Improved accessories; electri"ed water, oil, fuel injection, power steering pump, aircompressor 1 85 2.0 Accessories III: Auxiliary Power Unit 11-13 4834 6.4 Transmission I: 8-speed Automatic from 6-speed automatic 1 248 1.9 Transmission II: 6-Manual from 4-speed automatic 1 135 1.1 Transmission III: Automated Manual Transmission 2-13 4500 3.9 Diesel Engine I: aftertreatment improvements 1 109 5.0 Diesel Engine I 2 109 4.0 Diesel Engine II: low friction lubricants 1-13 3 1.0 Diesel Engine III: variable valve actuation 2 NA 1.1 Diesel Engine III 3-13 270 1.1 Diesel Engine IV: engine friction reduction, low tension piston rings, roller cam followers, piston skirt design, improved crankshaft design and bearings; coating 1-2 111 2.0 Diesel Engine IV: engine friction reduction, improved bearings to allow lower viscosity oil 3-4 225 2.0 Diesel Engine IV 5-13 225 2.0 Diesel Engine V: improved turbo efficiency 2 15 2.0 Diesel Engine V 3 15 2.0 Diesel Engine V 5-7 15 2.0 Diesel Engine V 4 15 2.0 Diesel Engine V 8-13 15 2.0 Diesel Engine VI: improved water, oil, fuel pump; pistons; valve train friction reduction 2 192 2.0 Diesel Engine VI 3 167 2.0 Diesel Engine VI 5-7 167 2.0 Diesel Engine VI: improved water, oil, and fuel pump; pistons 4 135 2.0 Diesel Engine VI 8-13 135 2.0 Diesel Engine VII: improved cylinder head, fuel rail and injector, EGR cooler 2 36 7.0 Diesel Engine VII 3 26 7.0 Diesel Engine VII 5-7 26 7.0 Diesel Engine VII 4 26 7.0 Diesel Engine VII 8-13 26 7.0 Diesel Engine VIII: turbo mechanical compounding 5-7 900 5.0 Diesel Engine VIII 8-13 900 5.0 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 85
Transportation Demand Module Table 7.16. High technology matrix for freight trucks (cont.)
Incremental Fuel Economy Vehicle Capital Costs Improvement Technology Type Category (2009$) (%)
Diesel Engine IX: low temperature EGR, improved turbochargers 1 166 6.0 Diesel Engine X: sequential downsizing/turbocharging 5-13 1080 2.8 Diesel Engine XI: waste heat recovery, Organic Rankine Cycle (bottoming cycle) 3-13 9000 8.8 Diesel Engine XII: electric turbo compounding 4-13 7200 10.0 Gasoline Engine I: low friction lubricants 1-13 3 0.6 Gasoline Engine II: coupled cam phasing 2-4 43 4.0 Gasoline Engine III: engine friction reduction; low tension piston rings, roller cam followers, piston skirt design, improved crankshaft design and bearings; coating 1 111 3.0 Gasoline III 2 104 3.0 Gasoline III 3-4 86 3.0 Gasoline Engine IV: stoichiometric gasoline direct injection V8 1-2 425 2.0 Gasoline Engine IV 3-4 430 2.0 Gasoline Engine V: turbocharging and downsizing SGDI V8 to V6 1-4 1569 2.2 Gasoline Engine VI: lean burn GDI 1-4 675 14.0 Gasoline Engine VII: HCCI 1-4 617 14.0 Hybrid System I: 42V engine off at idle 1-2 1350 7.7 Hybrid System I 3-4 1350 5.0 Hybrid System II: dual mode hybrid 1-2 10800 27.5 Hybrid System II: electric, ePTO, or hydraulic 3-4 24000 27.5 Hybrid System II: 4 kWh battery, 50 kW motor generator 5-13 24000 6.0 Source: Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol. 76, No. 179, (September 2011). Final Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, Regulatory Impact Analysis, U.S. Environmental Protection Agency and U.S. Department of Transportation, (August 2011). Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and CO2 Emissions, Final Report, TIAX, LLC. (October 2009). Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle Fuel Economy, Final Report, ICF International, Prepared for the U.S. Energy Information Administration, (August 2010). Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Research Council of the National Academy of Sciences, (2010).
+- [ [ \$"$ 46"=& "
Technology Introduction Year Fractional Efficiency Improvement Jet Fuel Trigger Price (1987$ per gallon)
Technology #1 2008 0.03 1.34 Technology #2 2014 0.07 1.34 Technology #3 2020 0.11 1.34 Technology #4 2025 0.15 1.34 Technology #5 2018 0.22 1.34 Technology #6 2018 0.10 1.34 Technology #7 2025 0.04 1.00 Technology #8 2020 0.05 0.00 Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009). Energy Information Administration, Transportation Sector Model of theNational Energy Modeling System, Model Documentation 2010, DOE/EIA-M070(2010), (Washington, DC, 2010).
86 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Transportation Demand Module Notes and sources
[1] U.S. Department of Transportation, National Highway Traffic and Safety Administration, Summary of Fuel Economy Performance, (Washington, DC, December 2009).
[2] Goldberg, Pinelopi Koujianou, Product Differentiation and Oligopoly In International Markets: The Case of The U.S.
Automobile Industry, Econometrica, Vol. 63, No.4 (July, 1995), 891-951.
[3] Oak Ridge National Laboratory, Fleet Characteristics and Data Issues, Stacy Davis and Lorena Truett, "nal report prepared for the Department of Energy, Energy Information Administration, Office of Energy Analysis, (Oak Ridge, Tn, January 2003).
[4] Bobit Publishing Company, The Fleet Fact Book, various issues (Redondo Beach, California).
[5] Bobit Publishing Company, Note 4.
[6] Davis, Stacy C., Lorena F. Truett, Investigation of Class 2B Trucks (Vehicles of 8,500 to 10,000 LBS GVWR), Oak Ridge National Laboratory, ORNL/TM-2002/49, March 2002.
[7] Davis, Stacy C., Lorena F. Truett, op.cit., Note 6.
[8] Greenspan, Alan, and Darrel Cohen, Motor Vehicle Stocks, Scrappage, and Sales, Federal Reserve Board (Washington, DC, October 30, 1996).
[9] Oak Ridge National Laboratory, Transportation Energy Data Book: 30th Edition (Oak Ridge, TN, 2011).
[10] Davis, Stacy C., Lorena F. Truett, op.cit., Note 6.
[11] Greene, David L. and S.M. Chin, Alternative Fuels and Vehicles (AFV) Model Changes, Center for Transportation Analysis, Oak Ridge National Laboratory, (Oak Ridge, TN, November 14, 2000).
[12] U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, prepared by Interlaboratory Working Group, Scenarios of U.S. Carbon Reductions: Potential Impacts of Energy Technologies by 2010 and Beyond, (Washington, DC, 1998).
[13] Energy and Environmental Analysis, Inc., Updates to the Fuel Economy Model (FEM) and Advanced Technology Vehicle (ATV) Module of the National Energy Modeling System (NEMS) Transportation Model, Prepared for the Energy Information Administration (EIA), (Arlington, VA, October 23, 2000).
[14] U.S. Energy Information Administration, Alternatives to Traditional Transportation Fuels 2005, http://www.eia.
doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use.
[15] U.S. Energy Information Administration, State Energy Data System 2009.
[16] Decision Analysis Corporation of Virginia, Re-estimation of Freight Adjustment Coefficients, Report prepared for the Energy Information Administration (EIA), February 28, 1995).
[17] Reebie Associates, TRANSEARCH Freight Commodity Flow Database, (Greenwich, CT, 1992).
[18] U.S. Department of Commerce, Bureau of Census, Vehicle Inventory and Use Survey, ECO2TV, (Washington, DC, December 2004).
[19] Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol.
76, No. 179, (September 2011).
[20] U.S. Department of Commerce, Bureau of the Census, Vehicle Inventory and U.S. Survey, ECO2TV (Washington, DC, December 2009).
[21] Decision Analysis Corporation of Virginia, op. cit. Note 19.
[22] Reebie Associates, op. cit., Note 17.
[23] Oak Ridge National Laboratory, Op. cit. Note 9.
[24] U.S. Department of Transportation, Federal Railroad Administration, 1989 Carload Waybill Statistics; Territorial Distribution, Traffic and Revenue by Commodity Classes, (September 1991 and Prior issues).
[25] U.S. Energy Information Administration, op. cit., Note 15.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 87
Transportation Demand Module Notes and sources
[26] U.S. Army Corps of Engineers, Waterborne Commerce of the United States, (Waterborne Statistics Center: New Orleans, LA, 1993).
[27] U.S. Energy Information Administration, op. cit., Note 15.
[28] U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics, Air Carrier Summary Data (Form 41, Schedules T-1 and T-2), (2011). http://www.transtats.bts.gov/DataIndex.
asp; link: Air Carrier Summary Data (Form 41 and 298C Summary Data).
[29] U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics, op. cit., Note 28.
[30] U.S. Department of Transportation, Federal Aviation Administration, Airport Capacity Benchmark Report, 2004 (2004).
[31] Jet Information Services Inc., World Jet Inventory: Year-End 2009, (December 2009).
[32] Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol.
76, No. 179, (September 2011).
[33] Energy Information Administration, op. cit. Note 14.
[34] Energy and Environmental Analysis, Inc., Documentation of Technologies Included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks, Prepared for the U.S. Energy Information Administration, (Arlington, VA, September 30, 2002).
[35] Final Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium-and Heavy-Duty Engines and Vehicles, Regulatory Impact Analysis, U.S. Environmental Protection Agency and U.S.
Department of Transportation, (August 2011).
[36] Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and CO2 Emissions, Final Report, TIAX, LLC.
(October 2009).
[37] Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle Fuel Economy, Final Report, ICF International, Prepared for the U.S. Energy Information Administration, (August 2010).
[38] Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Research Council of the National Academy of Sciences, (2010).
88 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module THIS PAGE INTENTIONALLY LEFT BLANK Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submoduleselectricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity "nance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2012, DOE/EIA-M068(2012).
Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.
EMM regions The supply regions used in EMM are based on the North American Electric Reliability Corporation regions and subregions shown in Figure 6.
Figure 6. Electricity Market Model Supply Regions U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 91
Electricity Market Module Model parameters and assumptions Generating capacity types The capacity types represented in the EMM are shown in Table 8.1.
Table 8.1. Generating capacity types represented in the Electricity Market Module Capacity Type Existing coal steam plants1 High Sulfur Pulverized Coal with Wet Flue Gas Desulfurization Advanced Coal - Integrated Coal Gasi"cation Combined Cycle Advanced Coal with carbon sequestration Oil/Gas Steam - Oil/Gas Steam Turbine Combined Cycle - Conventional Gas/Oil Combined Cycle Combustion Turbine Advanced Combined Cycle - Advanced Gas/Oil Combined Cycle Combustion Turbine Advanced Combined Cycle with carbon sequestration Combustion Turbine - Conventional Combustion Turbine Advanced Combustion Turbine - Steam Injected Gas Turbine Molten Carbonate Fuel Cell Conventional Nuclear Advanced Nuclear - Advanced Light Water Reactor Generic Distributed Generation - Baseload Generic Distributed Generation - Peak Conventional Hydropower - Hydraulic Turbine Pumped Storage - Hydraulic Turbine Reversible Geothermal Municipal Solid Waste Biomass - Fluidized Bed Solar Thermal - Central Tower Solar Photovoltaic - Fixed Tilt Wind Wind Offshore 1
The EMM represents 32 different types of existing coal steam plants, based on the different possible con"guration of NOx, particulate and SO2 emission control devices, as well as future options for controlling mercury.
Source: U.S. Energy Information Administration.
New generating plant characteristics The cost and performance characteristics of new generating technologies are inputs to the electricity capacity planning submodule (Table 8.2). These characteristics are used in combination with fuel prices from the NEMS fuel supply modules and foresight on fuel prices, to compare options when new capacity is needed. Heat rates for fossil-fueled technologies are assumed to decline linearly through 2025.
For the AEO2011, EIA commissioned an external consultant to develop current cost estimates for utility-scale electric generating plants [1]. This report continues to be the basis for the cost assumptions for AEO2012. A cost adjustment factor, based on the producer price index for metals and metal products, allows the overnight costs to fall in the future if this index drops, or rise further if it increases.
The overnight costs shown in Table 8.2 represent the estimated cost of building a plant in a typical region of the country.
Differences in plant costs due to regional distinctions are calculated by applying regional multipliers. Regional multipliers by technology were also updated for AEO2012 based on regional cost estimates developed by the consultant. The regional variations account for multiple factors, such as differences in terrain, weather, population, and labor wages. The base overnight cost is multiplied by a project contingency factor and a technological optimism factor (described later in this chapter), resulting in the total construction cost for the "rst-of-a-kind unit used for the capacity choice decision.
92 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module Table 8.2. Cost and performance characteristics of new central station electricity generating technologies Base Contingency Factors Total Overnight Overnight nth-of-a-Cost in Project Techno- Cost in Variable Fixed Heatrate6 kind Lead 2010 Contin- logical 20104 O&M5 O&M in 2011 Heatrate Online Size time (2010 $/ gency Optimism (2010 $/ (2010 $/ (2010$/ (Btu/ (Btu/
Technology Year1 (mW) (years) kW) Factor2 Factor3 kW) mWh) kW) KWh) KWh)
Scrubbed Coal New7 2015 1300 4 2,658 1.07 1.00 2,844 4.25 29.67 8,800 8,740 Integrated Coal-Gasi"cation Comb Cycle (IGCC)7 2015 1200 4 3,010 1.07 1.00 3,220 6.87 48.90 8,700 7,450 IGCC with carbon sequestration 2017 520 4 4,852 1.07 1.03 5,348 8.04 69.30 10,700 8,307 Conv Gas/Oil Comb Cycle 2014 540 3 931 1.05 1.00 977 3.43 14.39 7,050 6,800 Adv Gas/Oil Comb Cycle (CC) 2014 400 3 929 1.08 1.00 1,003 3.11 14.62 6,430 6,333 Adv CC with carbon sequestration 2017 340 3 1,834 1.08 1.04 2,060 6.45 30.25 7,525 7,493 Conv Comb Turbine8 2013 85 2 927 1.05 1.00 974 14.70 6.98 10,745 10,450 Adv Comb Turbine 2013 210 2 634 1.05 1.00 666 9.87 6.70 9,750 8,550 Fuel Cells 2014 10 3 5,918 1.05 1.10 6,836 0.00 350.00 9,500 6,960 Adv Nuclear 2017 2236 6 4,619 1.10 1.05 5,335 2.04 88.75 10,460 10,460 Distributed Generation - Base 2014 2 3 1,366 1.05 1.00 1,434 7.46 16.78 9,050 8,900 Distributed Generation - Peak 2013 1 2 1,640 1.05 1.00 1,722 7.46 16.78 10,056 9,880 Biomass 2015 50 4 3,519 1.07 1.02 3,859 5.00 100.55 13,500 13,500 Geothermal7,9 2011 50 4 2,393 1.05 1.00 2,513 9.64 108.62 9,760 9,760 MSW - Land"ll Gas 2011 50 3 7,694 1.07 1.00 8,233 8.33 378.76 13,648 13,648 Conventional Hydropower9 2015 500 4 2,134 1.10 1.00 2,347 2.55 14.27 9,760 9,760 Wind 2011 100 3 2,278 1.07 1.00 2,437 0.00 28.07 9,760 9,760 Wind Offshore 2015 400 4 4,345 1.10 1.25 5,974 0.00 53.33 9,760 9,760 Solar Thermal7 2014 100 3 4,384 1.07 1.00 4,691 0.00 64.00 9,760 9,760 Photovoltaic7,10 2013 150 2 4,528 1.05 1.00 4,755 0.00 16.70 9,760 9,760 1
Online year represents the "rst year that a new unit could be completed, given an order date of 2011. For wind, geothermal and land"ll gas, the online year was moved earlier to acknowledge the signi"cant market activity already occuring in anticipation of the expiration of the Production Tax Credit.
2 A contingency allowance is de"ned by the American Association of Cost Engineers as the speci"c provision for unforeseeable elements of costs within a de"ned project scope; particularly important where previous experience has shown that unforeseeable events which will increase costs are likely to occur.
3 The technological optimism factor is applied to the "rst four units of a new, unproven design; it re"ects the demonstrated tendency to underestimate actual costs for a "rst-of-a-kind unit.
4 Overnight capital cost including contingency factors, excluding regional multipliers and learning effects. Interest charges are also excluded. These represent costs of new projects initiated in 2011.
5 O&M = Operations and maintenance.
6 For hydro, geothermal, wind, and solar technologies, the heatrate shown represents the average heatrate for conventional thermal generation as of 2010.
This is used for purposes of calculating primary energy consumption displaced for these resources, and does not imply an estimate of their actual energy conversion efficiency.
7 Capital costs are shown before investment tax credits are applied.
8 Combustion turbine units can be built by the model prior to 2013 if necessary to meet a given regions reserve margin.
9 Because geothermal and hydro cost and performance characteristics are speci"c for each site, the table entries represent the cost of the least expensive plant that could be built in the Northwest Power Pool region, where most of the proposed sites are located.
10 Costs and capacities are expressed in terms of net AC power available to the grid for the installed capacity.
Sources: For the AEO2012 cycle, EIA continues to use the previously developed cost estimates for utility-scale electric generating plants, prepared by external consultants for AEO2011. This report can be found at www.eia.gov/oiaf/beck_plantcosts/index.html. Site-speci"c costs for geothermal were provided by the National Energy Renewable Laboratory, Updated U.S. Geothermal Supply Curve, February 2010.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 93
Electricity Market Module Technological optimism and learning Overnight costs for each technology are calculated as a function of regional construction parameters, project contingency, and technological optimism and learning factors.
The technological optimism factor represents the demonstrated tendency to underestimate actual costs for a "rst-of-a-kind, unproven technology. As experience is gained (after building 4 units) the technological optimism factor is gradually reduced to 1.0.
The learning function in NEMS is determined at a component level. Each new technology is broken into its major components, and each component is identi"ed as revolutionary, evolutionary or mature. Different learning rates are assumed for each component, based on the level of experience with the design component (Table 8.3). Where technologies use similar components, these components learn at the same rate as these units are built. For example, it is assumed that the underlying turbine generator for a combustion turbine, combined cycle and integrated coal-gasi"cation combined cycle unit is basically the same. Therefore construction of any of these technologies would contribute to learning reductions for the turbine component.
The learning function has the nonlinear form:
OC(C) = a*C-b, where C is the cumulative capacity for the technology component.
Table 8.3. Learning parameters for new generating technology components Period 1 Period 2 Period 3 Learning Rate Learning Learning Period 1 Period 2 Minimum Total Technology Component (LR1) Rate(LR2) Rate (LR3) Doublings Doublings Learning by 2025 Pulverized Coal - - 1% - - 5%
Combustion Turbine - conventional - - 1% - - 5%
Combustion Turbine - advanced - 10% 1% - 5 10%
1 HRSG - - 1% - - 5%
Gasi"er - 10% 1% - 5 10%
Carbon Capture/Sequestration 20% 10% 1% 3 5 20%
Balance of Plant - IGCC - - 1% - - 5%
Balance of Plant - Turbine - - 1% - - 5%
Balance of Plant - Combined Cycle - - 1% - - 5%
Fuel Cell 20% 10% 1% 3 5 20%
Advanced Nuclear 5% 3% 1% 3 5 10%
Fuel prep - Biomass 20% 10% 1% 3 5 20%
Distributed Generation - Base - 5% 1% - 5 10%
Distributed Generation - Peak - 5% 1% - 5 10%
Geothermal - 8% 1% - 5 10%
Municipal Solid Waste - - 1% - - 5%
Hydropower - - 1% - - 5%
Wind - - 1% - - 1%
Wind Offshore 20% 10% 1% 3 5 20%
Solar Thermal 20% 10% 1% 3 5 10%
Solar PV - Module 20% 10% 1% 1 5 10%
Balance of Plant - Solar PV 20% 10% 1% 1 5 10%
1 HRSG = Heat Recovery Steam Generator Note: Please see the text for a description of the methodology for learning in the Electricity Market Module.
Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis.
94 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module The progress ratio (pr) is de"ned by speed of learning (e.g., how much costs decline for every doubling of capacity). The reduction in capital cost for every doubling of cumulative capacity (LR) is an exogenous parameter input for each component (Table 8.3). The progress ratio and LR are related by:
pr = 2-b = (1 - LR)
The parameter b is calculated from the second equality above (b =-(ln(1-LR)/ln(2)). The parameter a is computed from initial conditions, i.e.
a =OC(C0)/CO-b where C0 is the initial cumulative capacity. Once the rates of learning (LR) and the cumulative capacity (C0) are known for each interval, the parameters (a and b) can be computed. Three learning steps were developed to re"ect different stages of learning as a new design is introduced into the market. New designs with a signi"cant amount of untested technology will see high rates of learning initially, while more conventional designs will not have as much learning potential. Costs of all design components are adjusted to re"ect a minimal amount of learning, even if new capacity additions are not projected. This represents cost reductions due to future international development or increased research and development.
Once the learning rates by component are calculated, a weighted average learning factor is calculated for each technology. The weights are based on the share of the initial cost estimate that is attributable to each component (Table 8.4). For technologies that do not share components, this weighted average learning rate is calculated exogenously, and input as a single component.
These technologies may still have a mix of revolutionary components and more mature components, but it is not necessary to include this detail in the model unless capacity from multiple technologies would contribute to the component learning. In the case of the solar PV technology, it is assumed that the module component accounts for 50 percent of the cost, and that the balance of system components accounts for the remaining 50 percent. Because the amount of end-use PV capacity (existing and projected) is signi"cant relative to total solar PV capacity, and because the technology of the module component is common across the end-use and electric power sectors, the calculation of the learning factor for the PV module component also takes into account capacity built in the residential and commercial sectors.
Table 8.5 shows the capacity credit toward component learning for the various technologies. It was assumed that for all combined-cycle technologies, the turbine unit contributed two-thirds of the capacity, and the steam unit one-third. Therefore, building one gigawatt of gas combined cycle would contribute 0.67 gigawatts toward turbine learning, and 0.33 gigawatts toward steam learning. Components that do not contribute to the capacity of the plant, such as the balance of plant category, receive 100 percent capacity credit for any capacity built with that component. For example, when calculating capacity for the Balance of plant - CC component, all combined cycle capacity would be counted 100 percent, both conventional and advanced.
Table 8.4. Component cost weights for new technologies Combus- Balance tion Combus- Carbon Balance of Turbine- tion Capture/ Balance of Plant-Pulverized conven- Turbine- Seques- of Plant- Plant- Combined Fuel Prep Technology Coal tional advanced HRSG Gasi"er tration IGCC Turbine Cycle Biomass Integrated Coal-Gasi"cation Comb Cycle (IGCC) 0% 0% 15% 20% 41% 0% 24% 0% 0% 0%
IGCC with carbon sequestration 0% 0% 10% 15% 30% 30% 15% 0% 0% 0%
Conv Gas/Oil Comb Cycle 0% 30% 0% 40% 0% 0% 0% 0% 30% 0%
Adv Gas/Oil Comb Cycle (CC) 0% 0% 30% 40% 0% 0% 0% 0% 30% 0%
Adv CC with carbon sequestration 0% 0% 20% 25% 0% 40% 0% 0% 15% 0%
Conv Comb Turbine 0% 50% 0% 0% 0% 0% 0% 50% 0% 0%
Adv Comb Turbine 0% 0% 50% 0% 0% 0% 0% 50% 0% 0%
Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 50%
Note: All unlisted technologies have a 100 percent weight with the corresponding component. Components are not broken out for all technologies unless there is overlap with other technologies.
HRSG = Heat Recovery Steam Generator.
Source: Market-Based Advanced Coal Power Systems, May 1999, DOE/FE-0400.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 95
Electricity Market Module Table 8.5. Component capacity weights for new technologies Combus-tion Combus- Carbon Balance of Turbine- tion Capture/ Balance Balance Plant-Pulverized conven- Turbine- Seques- of Plant- of Plant- Combined Fuel Prep Technology Coal tional advanced HRSG Gasi"er tration IGCC Turbine Cycle Biomass Integrated Coal-Gasi"cation Comb Cycle (IGCC) 0% 0% 67% 33% 100% 0% 100% 0% 0% 0%
IGCC with carbon sequestration 0% 0% 67% 33% 100% 100% 100% 0% 0% 0%
Conv Gas/Oil Comb Cycle 0% 67% 0% 33% 0% 0% 0% 0% 100% 0%
Adv Gas/Oil Comb Cycle (CC) 0% 0% 67% 33% 0% 0% 0% 0% 100% 0%
Adv CC with carbon sequestration 0% 0% 67% 33% 0% 100% 0% 0% 100% 0%
Conv Comb Turbine 0% 100% 0% 0% 0% 0% 0% 100% 0% 0%
Adv Comb Turbine 0% 0% 100% 0% 0% 0% 0% 100% 0% 0%
Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 100%
HRSG = Heat Recovery Steam Generator.
Source: U.S. Energy Information Administration, Office of Electricity, coal, Nuclear and Renewables Analysis.
Distributed generation Distributed generation is modeled in the end-use sectors (as described in the appropriate chapters) as well as in the EMM. This section describes the representation of distributed generation in the EMM only. Two generic distributed technologies are modeled.
The "rst technology represents peaking capacity (capacity that has relatively high operating costs and is operated when demand levels are at their highest). The second generic technology for distributed generation represents base load capacity (capacity that is operated on a continuous basis under a variety of demand levels). See Table 8.2 for costs and performance assumptions. It is assumed that these plants reduce the costs of transmission upgrades that would otherwise be needed.
Demand storage The electricity model includes the option to build a new demand storage technology to simulate load shifting, through programs such as smart meters. This is modeled as a new technology build, but with operating characteristics similar to pumped storage. The technology is able to decrease the load in peak slices, but must generate to replace that demand in other time slices. There is an input factor that identi"es the amount of replacement generation needed, where a factor of less than 1.0 can be used to represent peak shaving rather than purely shifting the load to other time periods. This plant type is limited to operating only in the peak load slices, and for AEO2012, it is assumed that this capacity is limited to 3 percent of peak demand on average, with limits varying from 2 percent to 6 percent of peak across the regions.
Representation of electricity demand The annual electricity demand projections from the NEMS demand modules are converted into load duration curves for each of the EMM regions (based on North American Electric Reliability Corporation regions and subregions) using historical hourly load data.
The load duration curve in the EMM is made up of 9 time slices. First, the load data is split into three seasons (winter - December through March, summer - June through September, and fall/spring). Within each season the load data is sorted from high to low, and three load segments are created - a peak segment representing the top 1 percent of the load, and then two off-peak segments representing the next 49 percent and 50 percent, respectively. The seasons were de"ned to account for seasonal variation in supply availability.
Reserve marginsthe percentage of capacity required in excess of peak demand needed for unforeseeable outagesare determined within the model through an iterative approach comparing the marginal cost of capacity and the cost of unserved energy. The target reserve margin is adjusted each model cycle until the two costs converge. The resulting reserve margins from the AEO2012 Reference case range from 8 to 21 percent.
96 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module Fossil fuel-"red and nuclear steam plant retirement Fossil-"red steam plant retirements and nuclear retirements are calculated endogenously within the model. Plants are assumed to retire when it is no longer economical to continue running them. Each year, the model determines whether the market price of electricity is sufficient to support the continued operation of existing plants. A plant is assumed to retire if the expected revenues from it are not sufficient to cover the annual going-forward costs and if the overall cost of producing electricity can be lowered by building new replacement capacity. The going-forward costs include fuel, operations and maintenance costs and annual capital additions, which are plant-speci"c and based on historical data. The average capital additions for existing plants are $8 per kilowatt (kW) for oil and gas steam plants, $16 per kW for coal plants and $22 per kW for nuclear plants (in 2010 dollars). These costs are added to the estimated costs at existing plants regardless of their age. Beyond 30 years of age an additional $6 per kW capital charge for fossil plants, and $32 per kW charge for nuclear plants is included in the retirement decision to re"ect further investment to address impacts of aging. Age-related cost increases are due to capital expenditures for major repairs or retro"ts, decreases in plant performance, and/or increased maintenance costs to mitigate the effects of aging.
EIA assumes all retirements reported as planned during the next ten years on the Form EIA-860 will occur. Additionally, the AEO2012 nuclear projection assumes an additional 5.5 gigawatts of nuclear plant retirements by 2035 based on the uncertainty related to resolving issues associated with long-term operations and aging management.
Biomass co-"ring Coal-"red power plants are assumed to co-"re with biomass fuel if it is economical. Co-"ring requires a capital investment for boiler modi"cations and fuel handling. This expenditure is assumed to be $274 per kW of biomass capacity. A coal-"red unit modi"ed to allow co-"ring can generate up to 15 percent of the total output using biomass fuel, assuming sufficient residue supplies are available.
Nuclear uprates The AEO2012 nuclear power projection assumes capacity increases at existing units. Nuclear plant operators can increase the rated capacity at plants through power uprates, which are license amendments that must be approved by the U.S. Nuclear Regulatory Commission (NRC). Uprates can vary from small (less than 2 percent) increases in capacity, which require very little capital investment or plant modi"cation, to extended uprates of 15-20 percent, requiring signi"cant modi"cations. Historically, most uprates were small, and the AEO projections accounted for them only after they were implemented and reported, but recent surveys by the NRC and EIA have indicated that more extended power uprates are expected in the near future. AEO2012 assumes that all of those uprates reported to EIA as planned modi"cations on the Form EIA-860 will take place, representing 0.8 gigawatts of additional capacity. EIA also assumes an additional 6.5 gigawatts of nuclear power uprates will be completed over the projection period, based on interactions with industry stakeholders and the NRC. Table 8.6 provides a summary of projected uprate capacity additions by region.
Table 8.6. Nuclear uprates by EMM region gigawatts Texas Reliability Entity 0.25 Florida Reliability Coordinating Council 0.67 Midwest Reliability Council - East 0.00 Midwest Reliability Council - West 0.49 Northeast Power Coordinating Council/New England 0.25 Northeast Power Coordinating Council/NYC-Westchester 0.00 Northeast Power Coordinating Council/Long Island 0.00 Northeast Power Coordinating Council/Upstate 0.50 ReliabilityFirst Corporation/East 0.82 ReliabilityFirst Corporation/Michigan 0.25 ReliabilityFirst Corporation/West 0.97 SERC Reliability Corporation/Delta 0.25 SERC Reliability Corporation/Gateway 0.00 SERC Reliability Corporation/Southeastern 0.25 SERC Reliability Corporation/Central 0.75 SERC Reliability Corporation/Virginia-Carolina 1.10 Southwest Power Pool/North 0.00 Southwest Power Pool/South 0.00 Western Electricity Coordinating Council/Southwest 0.25 Western Electricity Coordinating Council/California 0.50 Western Electricity Coordinating Council/Northwest Power Pool Area 0.00 Western Electricity Coordinating Council/Rockies 0.00 Total 7.31 Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis, based on Nuclear Regulatory Commission survey www.nrc.gov/reactors/operating/licensing/power-updates.html.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 97
Electricity Market Module Interregional electricity trade Both "rm and economy electricity transactions among utilities in different regions are represented within the EMM. In general, "rm power transactions involve the trading of capacity and energy to help another region satisfy its reserve margin requirement, while economy transactions involve energy transactions motivated by the marginal generation costs of different regions. The "ow of power from region to region is constrained by the existing and planned capacity limits as reported in the North American Electric Reliability Corporation and Western Electricity Coordinating Council Summer and Winter Assessment of Reliability of Bulk Electricity Supply in North America. Known "rm power contracts are obtained from NERCs Electricity Supply and Demand Database 2007 and information provided in the 2011 Summer and Winter Assessments. They are locked in for the term of the contract. Contracts that are scheduled to expire by 2016 are assumed not to be renewed. Because there is no information available about expiration dates for contracts that go beyond 2016, they are assumed to be phased out by 2025. The EMM includes an option to add interregional transmission capacity. In some cases it may be more economic to build generating capacity in a neighboring region, but additional costs to expand the transmission grid will be incurred as well. Explicitly expanding the interregional transmission capacity may also make the line available for additional economy trade.
Economy transactions are determined in the dispatching submodule by comparing the marginal generating costs of adjacent regions in each time slice. If one region has less expensive generating resources available in a given time period (adjusting for transmission losses and transmission capacity limits) than another region, the regions are assumed to exchange power.
International electricity trade Two components of international "rm power trade are represented in the EMMexisting and planned transactions, and unplanned transactions. Data on existing and planned transactions are obtained from the North American Electric Reliability Corporations Electricity Supply and Demand Database 2007. Unplanned "rm power trade is represented by competing Canadian supply with U.S. domestic supply options. Canadian supply is represented via supply curves using cost data from the Department of Energy report, Northern Lights: The Economic and Practical Potential of Imported Power from Canada, (DOE/PE-0079).
International economy trade is determined endogenously based on surplus energy expected to be available from Canada by region in each time slice. Canadian surplus energy is determined using Canadian electricity supply and demand projections from the MAPLE-C model developed for Natural Resources Canada.
Electricity pricing Electricity pricing is forecast for 22 electricity market regions in AEO2012 for fully competitive, partially competitive and fully regulated supply regions. The price of electricity to the consumer comprises the price of generation, transmission, and distribution including applicable taxes. Transmission and distribution are considered to remain regulated in the AEO; that is, the price of transmission and distribution is based on the average cost to build, operate and maintain these systems. In competitive regions, an algorithm in place allows customers to compete for better rates among rate classes as long as the overall average cost is met. The price of electricity in the regulated regions consists of the average cost of generation, transmission, and distribution for each customer class. In the competitive regions, the generation component of price is based on marginal cost, which is de"ned as the cost of the last (or most expensive) unit dispatched. The competitive generation price includes the marginal cost (fuel and variable operations and maintenance), taxes, and a reliability price adjustment, which represents what customers are willing to pay for added capacity to avoid outages in periods of high demand. The price of electricity in the regions with a competitive generation market consists of the competitive cost of generation summed with the average costs of transmission and distribution.
The price for mixed regions is a load-weighted average of the competitive price and the regulated price, based on the percent of electricity load in the region that has taken action to deregulate. In competitively supplied regions, a transition period is assumed to occur (usually over a ten-year period) from the effective date of restructuring, with a gradual shift to marginal cost pricing.
The Reference case assumes a transition to full competitive pricing in the three New York regions and in the ReliabilityFirst Corporation/ East region, and a 97-percent transition to competitive pricing in New England (Vermont being the only fully-regulated State in that region). Six regions fully regulate their electricity supply, including the Florida Reliability Coordinating Council, three of the SERC Reliability Corporation subregions - Southeastern (SRSE), Central (SRCE) and Virginia-Carolina (SRVC)
- Southwest Power Pool Regional Entity/North (SPNO), and the Western Electricity Coordinating Council / Rockies (RMPA). The Texas Reliability Entity, which in the past was considered fully competitive by 2010, now reaches only 88-percent competitive, since many cooperatives have declined to become competitive or allow competitive energy to be sold to their customers.
California returned to almost fully regulated pricing in 2002, after beginning a transition to competition in 1998, with only 7 percent competitive supply sold currently in the Western Electricity Coordinating Council (WECC)/ California region. All other regions are a mix of both competitive and regulated prices.
98 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module There have been ongoing changes to pricing structures for ratepayers in competitive States since the inception of retail competition. The AEO has incorporated these changes as they have been incorporated into utility tariffs. These have included transition period rate reductions and freezes instituted by various States, and surcharges in California relating to the 2000-2001 energy crisis there. Since price freezes for most customers have ended or will end in the next year or two, a large survey of utility tariffs found that many costs related to the transition to competition were now explicitly added to the distribution portion, and sometimes the transmission portion of the customer bill regardless of whether or not the customer bought generation service from a competitive or regulated supplier. There are some unexpected costs relating to unforeseen events. For instance, as a result of volatile fuel markets, State regulators have had a hard time enticing retail suppliers to offer competitive supply to residential and smaller commercial and industrial customers. They have often resorted to procuring the energy themselves through auction or competitive bids or have allowed distribution utilities to procure the energy on the open market for their customers for a fee.
For AEO2012, typical charges that all customers must pay on the distribution portion of their bill (depending on where they reside) include: transition charges (including persistent stranded costs), public bene"ts charges (usually for efficiency and renewable energy programs), administrative costs of energy procurement, and nuclear decommissioning costs. Costs added to the transmission portion of the bill include the Federally Mandated Congestion Charges (FMCC), a bill pass-through associated with the Federal Energy Regulatory Commission passage of Standard Market Design (SMD) to enhance reliability of the transmission grid and control congestion. Additional costs not included in historical data sets have been added in adjustment factors to the transmission and distribution operations and maintenance costs, which impact the cost of both competitive and regulated electricity supply. Since most of these costs, such as transition costs, are temporary in nature, they are gradually phased out throughout the forecast. Regions found to have these added costs include the Northeast Power Coordinating Council/ New England and New York regions, the ReliabilityFirst Corporation/ East and West regions, and the WECC/ California region.
Fuel price expectations Capacity planning decisions in the EMM are based on a life cycle cost analysis over a 30-year period. This requires foresight assumptions for fuel prices. Expected prices for coal, natural gas and oil are derived using rational expectations, or perfect foresight. In this approach, expectations for future years are de"ned by the realized solution values for these years in a prior run.
The expectations for the world oil price and natural gas wellhead price are set using the resulting prices from a prior run. The markups to the delivered fuel prices are calculated based on the markups from the previous year within a NEMS run. Coal prices are determined using the same coal supply curves developed in the Coal Market Module. The supply curves produce prices at different levels of coal production, as a function of labor productivity, and costs and utilization of mines. Expectations for each supply curve are developed in the EMM based on the actual demand changes from the prior run throughout the projection horizon, resulting in updated mining utilization and different supply curves.
The perfect foresight approach generates an internally consistent scenario for which the formation of expectations is consistent with the projections realized in the model. The NEMS model involves iterative cycling of runs until the expected values and realized values for variables converge between cycles.
Nuclear fuel prices Nuclear fuel prices are calculated through an offline analysis which determines the delivered price to generators in mills per kilowatthour. To produce reactor grade uranium, the uranium (U308) must "rst be mined, and then sent through a conversion process to prepare for enrichment. The enrichment process takes the fuel to a given purity of U-235, typically 3-5 percent for commercial reactors in the United States. Finally, the fabrication process prepares the enriched uranium for use in a speci"c type of reactor core. The price of each of the processes is determined, and the prices are summed to get the "nal price of the delivered fuel. The one mill per kilowatthour charge that is assessed on nuclear generation to go to the DOEs Nuclear Waste Fund is also included in the "nal nuclear price. The analysis uses forecasts from Energy Resources International for the underlying uranium prices.
Legislation and regulations Clean Air Act Amendments of 1990 (CAAA90) and Cross-State Air Pollution Rule (CSAPR)
The Cross-State Air Pollution Rule (CSAPR) was released by EPA in July 2011 and was created to regulate SO2 and NOx emissions from coal, oil, and natural gas steam power plants. CSAPR is intended to help States meet their National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter. CSAPR implementation has been delayed because of a stay issued by the U.S. Court of Appeals for the D.C. Circuit. However, it is included in AEO2012 despite the stay, because the Court of Appeals had not made a "nal ruling at the time AEO2012 was completed.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 99
Electricity Market Module CSAPR puts limits on annual emissions of SO2 and NOx, as well as seasonal NOx limits to address ground-level ozone. Twenty-three States are subject to the annual limits, and 25 States are subject to the seasonal limits. CSAPR consists of four individual cap and trade programs, covering two different SO2 groups, the Annual NOx group and the Seasonal NOx group (Figure 7). Each program was scheduled to begin in January 2012 with an initial annual cap, and for the Group 1 SO2 program, the cap is reduced further in 2014.
As speci"ed in the CAAA90, EPA has developed a two-phase nitrogen oxide (NOx) program, with the "rst set of standards for existing coal plants applied in 1996 while the second set was implemented in 2000. Dry bottom wall-"red, and tangential-"red boilers, the most common boiler types, referred to as Group 1 Boilers, were required to make signi"cant reductions beginning in 1996 and further reductions in 2000. Relative to their uncontrolled emission rates, which range roughly between 0.6 and 1.0 pounds per million Btu, they are required to make reductions between 25 and 50 percent to meet the Phase I limits and further reductions to meet the Phase II limits. The EPA did not impose limits on existing oil and gas plants, but some states have additional NOx regulations. All new fossil units are required to meet standards. In pounds per million Btu, these limits are 0.11 for conventional coal, 0.02 for advanced coal, 0.02 for combined cycle, and 0.08 for combustion turbines. These NOx limits are incorporated in EMM.
Figure 7. States covered by CSAPR limits on sulfur dioxide and nitrogen oxide emissions Source: U.S. Energy Information Administration.
100 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module Sample costs of adding "ue gas desulfurization equipment (FGD) to remove sulfur dioxide (SO2) and selective catalytic reduction (SCR) equipment to remove nitrogen oxides (NOx) are given below for 100, 300, 500, and 700-megawatt coal plants. In the EMM, plant-speci"c costs are calculated based on the size of the unit and other operating characteristics.
FGD units are assumed to remove 95 percent of the SO2, while SCR units are assumed to remove 90 percent of the NOx. For AEO2012, the EMM also includes an option to install a dry sorbent injection (DSI) system, which is assumed to remove 70 percent of the SO2. However, the DSI option is only available under the mercury and air toxics rule discussed in the next section, as its primary bene"t is for reducing hydrogen chloride (HCl). The costs per megawatt of capacity decline with plant size and are shown in Table 8.7.
+- 7 [ ! "" " "
2010 dollars Coal Plant Size (MW) FGD Capital Costs ($/kw) SCR Capital Costs ($/kw) DSI Capital Costs ($/kw) 100 642 222 125 300 497 187 57 500 432 174 40 700 360 155 31 Documentation for EPA Base Case v4.10 using the Integrated Planning Model, August 2010, EPA Contract EP-W-08-018.
Mercury regulation The Mercury and Air Toxics Standards (MATS) rule was "nalized in December 2011 to ful"ll EPAs requirement to regulate mercury emissions from power plants. MATS also regulates other hazardous air pollutants (HAPS) such as hydrogen chloride (HCl) and "ne particulate matter (PM2.5). The rule applies to coal- and oil-"red power plants with a nameplate capacity greater than 25 megawatts. The standards are scheduled to take effect in 2015 and require that all qualifying units achieve the maximum achievable control technology (MACT) for each of the three covered pollutants. For AEO2012, EIA assumes that all coal-"red generating units with a capacity greater than 25 megawatts will comply with the rule beginning in 2015. All power plants are required to reduce their mercury emissions to 90 percent below their uncontrolled emissions levels.
Because the EMM does not explicitly model HCl or PM2.5, speci"c control technologies are assumed to be used to achieve compliance. In order to meet the HCl requirement, units must have either "ue gas desulfurization (FGD) scrubbers or dry sorbent injection (DSI) systems in order to continue operating. A full fabric "lter is also required to meet the PM2.5 limits and to improve the effectiveness of the DSI technology. For mercury reductions, the EMM allows plants to alter their con"guration by adding equipment, such as an SCR to remove NOx or an SO2 scrubber. They can also add activated carbon injection systems speci"cally designed to remove mercury. Activated carbon can be injected in front of existing particulate control devices or a supplemental fabric "lter can be added with activated carbon injection capability.
The equipment to inject activated carbon in front of an existing particulate control device is assumed to cost approximately $6 (2010 dollars) per kilowatt of capacity, while the cost of a supplemental fabric "lter with activated carbon injection (often referred as a COPAC unit) is approximately $150 (2010 dollars) per kilowatt of capacity [2]. The amount of activated carbon required to meet a given percentage removal target is given by the following equations [3].
For a unit with a CSE, using subbituminous coal, and simple activated carbon injection:
t Hg Removal (%) = 65 - (65.286 / (ACI + 1.026))
For a unit with a CSE, using bituminous coal, and simple activated carbon injection:
t Hg Removal (%) = 100 - (469.379 / (ACI + 7.169))
For a unit with a CSE, and a supplemental fabric "lter with activated carbon injection:
t Hg Removal (%) = 100 - (28.049 / (ACI + 0.428))
For a unit with a HSE/Other, and a supplemental fabric "lter with activated carbon injection:
t Hg Removal (%) = 100 - (43.068 / (ACI + 0.421))
ACI = activated carbon injected in pounds per million actual cubic feet.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 101
Electricity Market Module Power plant mercury emissions assumptions The EMM represents 35 coal plant con"gurations and assigns a mercury emissions modi"cation factor (EMF) to each con"guration.
Each con"guration represents different combinations of boiler types, particulate control devices, sulfur dioxide (SO2) control devices, nitrogen oxide (NOx) control devices, and mercury control devices. An EMF represents the amount of mercury that was in the fuel that remains after passing through all the plants systems. For example, an EMF of 0.60 means that 40 percent of the mercury that was in the fuel is removed by various parts of the plant. Table 8.8 provides the assumed EMFs for existing coal plant con"gurations without mercury-speci"c controls.
+- 7 7 <46 6 " &"
Con"guration EIA EMFs EPA EMFs NOx SO2 Control Particulate Control Control Bit Coal Sub Coal Lignite Coal Bit Coal Sub Coal Lignite Coal None BH -- 0.11 0.27 0.27 0.11 0.26 1.00 Wet BH None 0.05 0.27 0.27 0.03 0.27 1.00 Wet BH SCR 0.10 0.27 0.27 0.10 0.15 0.56 Dry BH -- 0.05 0.75 0.75 0.50 0.75 1.00 None CSE -- 0.64 0.97 0.97 0.64 0.97 1.00 Wet CSE None 0.34 0.73 0.73 0.34 0.84 0.56 Wet CSE SCR 0.10 0.73 0.73 0.10 0.34 0.56 Dry CSE -- 0.64 0.65 0.65 0.64 0.65 1.00 None HSE/Oth -- 0.90 0.94 0.94 0.90 0.94 1.00 Wet HSE/Oth None 0.58 0.80 0.80 0.58 0.80 1.00 Wet HSE/Oth SCR 0.42 0.76 0.76 0.10 0.75 1.00 Dry HSE/Oth -- 0.60 0.85 0.85 0.60 0.85 1.00 Notes: SO2 Controls - Wet = Wet Scrubber and Dry = Dry Scrubber, Particulate Controls, BH - fabric "lter/baghouse. CSE = cold side electrostatic precipitator, HSE = hot side electrostatic precipitator, NOx Controls, SCR = selective catalytic reduction,
= not applicable, Bit = bituminous coal, Sub = subbituminous coal. The NOx control system is not assumed to enhance mercury removal unless a wet scrubber is present, so it is left blank in such con"gurations. Sources: EPA, EMFs. www.epa.gov/clearskies/technical.html. EIA EMFs not from EPA: Lignite EMFs, Mercury Control Technologies for Coal-Fired Power Plants, presented by the Office of Fossil Energy on July 8, 2003. Bituminous coal mercury removal for a Wet/HSE/Oth/SCR con"gured plant, Table EMF1, Analysis of Mercury Control Cost and Performance, Office of Fossil Energy & National Energy Technology Laboratory, U.S. Department of Energy, January 2003, Washington, DC.
Planned SO2 Scrubber and NOx control equipment additions EIA assumes that all planned retro"ts, as reported on the Form EIA-860, will occur as currently scheduled. For AEO2012, this includes 10.8 gigawatts of planned SO2 scrubbers (Table 8.9) and 4.5 gigawatts of planned selective catalytic reduction (SCR).
Carbon capture and sequestration retro"ts Although a Federal greenhouse gas program is not assumed in the AEO2012 Reference case, the EMM includes the option of retro"tting existing coal plants for carbon capture and sequestration (CCS). This option is important when considering alternate scenarios that do constrain carbon emissions. The modeling structure for CCS retro"ts within the EMM was developed by the National Energy Technology Laboratory[4] and uses a generic model of retro"t costs as a function of basic plant characteristics (such as heatrate). The costs have been adjusted to be consistent with costs of new CCS technologies. The CCS retro"ts are assumed to remove 90 percent of the carbon input. The addition of the CCS equipment results in a capacity derate of around 30 percent and reduced efficiency of 43 percent at the existing coal plant. The costs depend on the size and efficiency of the plant, with the capital costs ranging from $1,110 to $1,620 per kilowatt. It was assumed that only plants greater than 500 megawatts and with heat rates below 12,000 BTU per kilowatthour would be considered for CCS retro"ts.
State Air Emissions Regulation AEO2012 continues to model the Northeast Regional Greenhouse Gas Initiative (RGGI), which applies to fossil-fuel powered plants over 25 megawatts in the Northeastern United States. The State of New Jersey withdrew from the program at the end of 2011, leaving nine States in the accord. The rule caps CO2 emissions from covered electricity generating facilities and requires that they account for each ton of CO2 emitted with an allowance purchased at auction. Because the baseline and projected emissions were calculated before the economic recession that began in 2008, the actual emissions in the "rst years of the program have been less than the cap, leading to excess allowances and allowance prices at the "oor price.
102 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module The California Assembly Bill 32 (AB 32), the Global Warming Solutions Act of 2006, authorized the California Air Resources Board (CARB) to set Californias GHG reduction goals for 2020 and establish a comprehensive, multi-year program to reduce GHG emissions in California. As one of the major initiatives for AB 32, CARB designed a cap-and-trade program that started on January 1, 2012, with the enforceable compliance obligations beginning in 2013. Although the cap-and-trade program applies to multiple economic sectors, for AEO2012 it is only assumed to be implemented in the electric power sector. The electric power sector represented 25 percent of the States GHG emissions in 2008, and therefore the EMM modeled the power sector cap at 25 percent of the limits speci"ed in the bill for all sectors.
Table 8.9. Planned SO2 scrubber additions by EMM region gigawatts Texas Reliability Entity 0.0 Florida Reliability Coordinating Council 0.0 Midwest Reliability Council - East 0.0 Midwest Reliability Council - West 0.0 Northeast Power Coordinating Council/New England 0.0 Northeast Power Coordinating Council/NYC-Westchester 0.0 Northeast Power Coordinating Council/Long Island 0.0 Northeast Power Coordinating Council/Upstate 1.0 ReliabilityFirst Corporation/East 1.2 ReliabilityFirst Corporation/Michigan 0.0 ReliabilityFirst Corporation/West 4.4 SERC Reliability Corporation/Delta 0.0 SERC Reliability Corporation/Gateway 0.0 SERC Reliability Corporation/Southeastern 4.1 SERC Reliability Corporation/Central 0.2 SERC Reliability Corporation/Virginia-Carolina 0.0 Southwest Power Pool/North 0.0 Southwest Power Pool/South 0.0 Western Electricity Coordinating Council/Southwest 0.0 Western Electricity Coordinating Council/California 0.0 Western Electricity Coordinating Council/Northwest Power Pool Area 0.0 Western Electricity Coordinating Council/Rockies 0.0 Total 10.8 Source: U.S. Energy Information Administration, Form EIA-860, Annual Electric Generator Report.
Energy Policy Acts of 1992 (EPACT92) and 2005 (EPACT05)
The provisions of the EPACT92 include revised licensing procedures for nuclear plants and the creation of exempt wholesale generators (EWGs). The EPACT05 provides a 20-percent investment tax credit for Integrated Coal-Gasi"cation Combined Cycle capacity and a 15-percent investment tax credit for other advanced coal technologies. These credits are limited to 3 gigawatts in both cases. It also contains a production tax credit (PTC) of 1.8 cents (nominal) per kilowatthour for new nuclear capacity beginning operation by 2020. This PTC is speci"ed for the "rst 8 years of operation, is limited to $125 million (per gigawatt) annually, and is limited to 6 gigawatts of new capacity. However, this credit may be shared to additional units if more than 6 gigawatts are under construction by January 1, 2014. EPACT05 extended the PTC for qualifying renewable facilities by 2 years, or December 31, 2007. It also repealed the Public Utility Holding Company Act (PUHCA).
Energy Improvement and Extension Act 2008 (EIEA2008)
EIEA2008 extended the investment tax credit of 30 percent through 2016 for solar and fuel cell facilities.
American Recovery and Reinvestment Act (ARRA)
Updated tax credits for Renewables ARRA extended the expiration date for the PTC to January 1, 2013, for wind and January 1, 2014, for all other eligible renewable resources. In addition, ARRA allows companies to choose an investment tax credit (ITC) of 30 percent in lieu of the PTC and allows for a grant in lieu of this credit to be funded by the U.S. Treasury. For some technologies, such as wind, the full PTC would appear to be more valuable than the 30 percent ITC; however, the difference can be small. Qualitative factors, such as the lack of partners with sufficient tax liability, may cause companies to favor the ITC grant option. AEO2012 generally assumes that renewable electricity projects will claim the more favorable tax credit or grant option available to them.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 103
Electricity Market Module Loan guarantees for renewables ARRA provided $6 billion to pay the cost of guarantees for loans authorized by the Energy Policy Act of 2005. While most renewable projects which start construction prior to September 30, 2011 are potentially eligible for these loan guarantees, the application and approval of guarantees for speci"c projects is a highly discretionary process, and has thus far been limited. While AEO2012 includes projects that have received loan guarantees under this authority, it does not assume automatic award of the loans to potentially eligible technologies.
Support for CCS ARRA provided $3.4 billion for additional research and development on fossil energy technologies. A portion of this funding is expected to be used to fund projects under the Clean Coal Power Initiative program, focusing on projects that capture and sequester greenhouse gases. To re"ect the impact of this provision, AEO2012 Reference case assumes that an additional 1 gigawatt of coal capacity with CCS will be stimulated by 2017.
Smart grid expenditures ARRA provides $4.5 billion for smart grid demonstration projects. While somewhat difficult to de"ne, smart grid technologies generally include a wide array of measurement, communications, and control equipment employed throughout the transmission and distribution system that will enable real-time monitoring of the production, "ow, and use of power from generator to consumer.
Among other things, these smart grid technologies are expected to enable more efficient use of the transmission and distribution grid, lower line losses, facilitate greater use of renewables, and provide information to utilities and their customers that will lead to greater investment in energy efficiency and reduced peak load demands. The funds provided will not fund a widespread implementation of smart grid technologies, but could stimulate more rapid investment than would otherwise occur.
Several changes were made throughout the NEMS to represent the impacts of the smart grid funding provided in ARRA. In the electricity module, it was assumed that line losses would fall slightly, peak loads would fall as customers shifted their usage patterns, and customers would be more responsive to pricing signals. Historically, line losses, expressed as the percentage of electricity lost, have been falling for many years as utilities make investments to replace aging or failing equipment.
Smart grid technologies also have the potential to reduce peak demand through the increased deployment of demand response programs. In AEO2012, it is assumed that the Federal expenditures on smart grid technologies will stimulate efforts that reduce peak demand in 2035 by 3 percent from what they otherwise would be. Load is shifted to offpeak hours, so net energy consumed remains largely constant.
FERC Orders 888 and 889 FERC has issued two related rules (Orders 888 and 889) designed to bring low-cost power to consumers through competition, ensure continued reliability in the industry, and provide for open and equitable transmission services by owners of these facilities.
Speci"cally, Order 888 requires open access to the transmission grid currently owned and operated by utilities. The transmission owners must "le nondiscriminatory tariffs that offer other suppliers the same services that the owners provide for themselves.
Order 888 also allows these utilities to recover stranded costs (investments in generating assets that are unrecoverable due to consumers selecting another supplier). Order 889 requires utilities to implement standards of conduct and an Open Access Same-Time Information System (OASIS) through which utilities and non-utilities can receive information regarding the transmission system. Consequently, utilities are expected to functionally or physically unbundle their marketing functions from their transmission functions.
These orders are represented in EMM by assuming that all generators in a given region are able to satisfy load requirements anywhere within the region. Similarly, it is assumed that transactions between regions will occur if the cost differentials between them make such transactions economical.
Electricity alternative cases Integrated Technology cases The Integrated High Technology Cost case combines assumptions from the end-use High Technology cases with assumptions on lower costs of new power plants, including renewables, nuclear and fossil. Assumptions for the other sectors appear in the respective chapters. This case assumes that the capital and operating costs for new fossil and nuclear plants will start 20 percent lower than in the Reference case, and will be 40 percent lower than Reference case levels in 2035.
The Integrated 2011 technology case combines assumptions from the end-use 2011 Technology cases and higher costs for new power plants. In the EMM it is assumed that the base costs of all nuclear and fossil generating technologies will remain at current costs during the projection period, with no reductions due to learning. The annual commodity cost adjustment factor is still applied as in the Reference case.
104 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module Table 8.10 shows the costs assumed for new fossil technologies across the Integrated Technology cases, while Table 8.11 shows the costs for new nuclear plants in the same cases.
Table 8.10. Cost and performance characteristics for fossil-fueled generating technologies: three cases Total Overnight Cost1 Total Overnight Cost Low Integrated High Integrated in 2012 (Reference) Reference Technology Technology (2010$/kW) (2010$/kW) (2010$/kW) (2010$/kW)
Pulverized Coal 2844 2015 2985 3005 2311 2020 2784 2830 2034 2025 2597 2666 1784 2030 2354 2449 1515 2035 2115 2229 1269 Advanced Coal 3220 2015 3366 3403 2604 2020 3100 3204 2265 2025 2865 3019 1968 2030 2565 2773 1651 2035 2281 2524 1368 Advanced Coal with Sequestration 5348 2015 5564 5650 4306 2020 5094 5321 3721 2025 4673 5013 3209 2030 4155 4605 2674 2035 3662 4191 2197 Conventional Combined Cycle 977 2015 1026 1033 794 2020 956 972 698 2025 892 916 614 2030 809 841 520 2035 727 766 436 Advanced Gas 1003 2015 1050 1060 813 2020 963 998 703 2025 890 940 611 2030 795 864 511 2035 706 786 424 Advanced Gas with Sequestration 2060 2015 2141 2177 1657 2020 1949 2050 1423 2025 1782 1931 1224 2030 1576 1774 1014 2035 1383 1614 829 Conventional Combustion Turbine 974 2015 1022 1029 790 2020 953 969 696 2025 889 913 610 2030 806 838 518 2035 724 763 434 Advanced Combustion Turbine 666 2015 695 704 538 2020 631 663 461 2025 579 624 398 2030 512 573 329 2035 451 522 270 1
Total overnight cost (including project contingency, technological optimism and learning factors, but excluding regional multipliers), for projects online in the given year.
Source: U.S. Energy Information Administration. AEO2012 National Energy Modeling System runs: REF2012.D020112C, LTRKITEN.D031312A, HTRKITEN.D032812A U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 105
Electricity Market Module Table 8.11. Cost characteristics for advanced nuclear technology: three cases Total Overnight Cost1 Overnight Cost Low Integrated High Integrated in 2012 (Reference) Reference Technology Technology (2010$/kW) (2010$/kW) (2010$/kW) (2010$/kW)
Advanced Nuclear 5335 2015 5466 5638 4231 2020 4733 5309 3456 2025 4302 5002 2954 2030 3850 4594 2477 2035 3414 4181 2049 1
Total overnight cost (including project contingency, technological optimism and learning factors, but excluding regional multipliers), for projects online in the given year.
Source: U.S. Energy Information Administration. AEO2012 National Energy Modeling System runs: REF2012.D020112C, LTRKITEN.
D031312A, HTRKITEN.D032812A.
Electricity Environmental Regulation cases Over the next few years electricity generators will have to begin steps to comply with a number of new environmental-Regulations, primarily through adding environmental controls at existing coal power plants. The additional cases examine the impacts of shorter economic recovery periods for the environmental controls, both with natural gas prices similar to the AEO2012 reference case and with lower natural gas prices.
t The Reference 5 case assumes that the economic recovery period for investments in new environmental controls is reduced from 20 years to 5 years.
t The Low Gas Price 5 case uses more optimistic assumptions about future volumes of shale gas production, leading to lower natural gas prices, combined with the "ve-year recovery period for new environmental controls. The domestic shale gas resource assumption comes from the Low Tight Oil and Shale Gas Resource case.
Nuclear Alternative cases For AEO2012, two alternate cases were run for nuclear power plants to address uncertainties about the operating lives of existing reactors, the potential for new nuclear capacity, and capacity uprates at existing plants. These scenarios are discussed in the Issues in Focus article, Nuclear Power in AEO2012 in the full AEO2012 report.
t The Low Nuclear case assumes that all existing nuclear plants are retired after 60 years of operation. In the Reference case, existing plants are assumed to run as long as they continue to be economic, implicitly assuming that a second 20-year license renewal will be obtained for most plants reaching 60 years before 2035. This case was run to analyze the impact of additional nuclear retirements, which could occur if the oldest plants do not receive a second license extension. In this case, 31 gigawatts of nuclear capacity are assumed to be retired by 2035. his case assumes that no new nuclear capacity will be added throughout the projection, excluding the capacity already planned and under construction. The case also assumes that only those capacity uprates reported to EIA will be completed. The Reference case assumes additional uprates based on Nuclear Regulatory Commission (NRC) surveys and industry reports.
t The High Nuclear case assumes that all existing nuclear units will receive a second license renewal and operate beyond 60 years (excluding one announced retirement). In the Reference case, beyond the announced retirement of Oyster Creek, an additional 5.5 gigawatts of nuclear capacity is assumed to be retired through 2035, re"ecting uncertainty surrounding future aging impacts and/or costs. This case was run to provide a more optimistic outlook where all licenses are renewed and all plants are assumed to "nd it economic to continue operating beyond 60 years. The High Nuclear case also assumes additional planned nuclear capacity is completed based on combined license (COL) applications with the NRC. The Reference case assumes 6.8 gigawatts of planned capacity are added, while the High Nuclear case includes 13.5 gigawatts of planned capacity additions.
106 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Electricity Market Module Notes and sources
[1] Updated Capital Cost Estimates for Electricity Generation Plants, EIA, November 2010.
[2] These costs were developed using the National Energy Technology Laboratory Mercury Control Performance and Cost Model, 1998.
[3] U.S. Department of Energy, Analysis of Mercury Control Cost and Performance, Office of Fossil Energy & National Energy Technology Laboratory, January 2003.
[4] Retro"tting Coal-Fired Power Plants for Carbon Dioxide Capture and Sequestration - Exploratory Testing of NEMS for Integrated Assessments, DOE/NETL-2008/1309, P.A. Geisbrecht, January 18, 2009.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 107
THIS PAGE INTENTIONALLY LEFT BLANK Oil and Gas Supply Module THIS PAGE INTENTIONALLY LEFT BLANK Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply Submodule[1], and Alaska Oil and Gas Supply Submodule. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2011), (Washington, DC, 2011). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous "rms that produce oil and natural gas from domestic "elds throughout the United States.
Figure 8. Oil and Gas Supply Model regions Rocky Mountain - 5 West Coast Rocky Mountains Northeast Midcontinent Atlantic Southwest Gulf Coast Shallow Gulf of Mexico Deep Gulf of Mexico Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 111
Oil and Gas Supply Module OGSM encompasses domestic crude oil and natural gas supply by several recovery techniques and sources. Crude oil recovery includes improved oil recovery processes such as water "ooding, in"ll drilling, and horizontal continuity, as well as enhanced oil recovery processes such as CO2 "ooding, steam "ooding, and polymer "ooding. Recovery from highly fractured, continuous zones (e.g. Austin chalk and Bakken shale formations) is also included. Natural gas supply includes resources from low-permeability tight sand formations, shale formations, coalbed methane, and other sources.
Key assumptions Domestic oil and natural gas technically recoverable resources Domestic oil and natural gas technically recoverable resources [2] consist of proved reserves [3] and unproved resources [4].
OGSM resource assumptions are based on estimates of technically recoverable resources from the United States Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) of the Department of the Interior [5]. Supplemental adjustments to the USGS continuous crude oil and natural gas resources are made to incorporate the latest available production data and to add some frontier plays that are not quantitatively assessed by the USGS. While undiscovered resources for Alaska are based on USGS estimates, estimates of recoverable resources are obtained on a "eld-by-"eld basis from a variety of sources including trade press. Published estimates in Tables 9.1 and 9.2 re"ect the removal of intervening reserve additions between the date of the latest available assessment and January 1, 2010.
Table 9.1. Technically recoverable U.S. crude oil resources as of January 1, 2010 billion barrels Total Technically Proved Reserves Unproved Resources Recoverable Resources Lower 48 Onshore 14.2 112.6 126.7 Northeast 0.2 4.4 4.6 Gulf Coast 1.5 21.4 22.8 Midcontinent 1.3 12.7 14.0 Southwest 5.3 27.6 32.9 Rocky Mountain 3.2 23.0 26.2 West Coast 2.7 23.5 26.2 Lower 48 Offshore 4.6 50.3 54.8 Gulf (currently available) 4.1 38.7 42.7 Eastern/Central Gulf (unavailable until 2022) 0.0 3.7 3.7 Paci"c 0.5 6.6 7.1 Atlantic 0.0 1.4 1.4 Alaska (Onshore and Offshore) 3.6 35.0 38.6 Total U.S. 22.3 197.9 220.2 Note: Crude oil resources include lease condensates but do not include natural gas plant liquids or kerogen (oil shale). Resources in areas where drilling is officially prohibited are not included in this table. The estimate of 7.3 billion barrels of crude oil resources in the Northern Atlantic, Northern and Central Paci"c, and within a 50-mile buffer off the Mid and Southern Atlantic OCS is also excluded from the technically recoverable volumes because leasing is not expected in these areas by 2035.
Source: Onshore, State Offshore, and Alaska - U.S. Geological Survey (USGS); Federal (Outer Continental Shelf) Offshore - Bureau of Ocean Energy Management (formerly the Minerals Management Service); Proved Reserves - U.S. Energy Information Administration. Table values re"ect removal of intervening reserve additions between the date of the latest available assessment and January 1, 2010.
Lower 48 onshore The Onshore Lower 48 Oil and Gas Supply Submodule (OLOGSS) is a play-level model used to analyze crude oil and natural gas supply from onshore lower 48 sources. The methodology includes a comprehensive assessment method for determining the relative economics of various prospects based on "nancial considerations, the nature of the resource, and the available technologies. The play-level unproved technically recoverable resource assumptions for tight oil, shale gas, tight gas, and coalbed methane are shown in Tables 9.3-9.6. The general methodology relies on a detailed economic analysis of potential projects in known "elds, enhanced oil recovery projects, and undiscovered resources. The projects which are economically viable are developed subject to the availability of resource development constraints which simulate the existing and expected infrastructure of the oil and gas industries. For crude oil projects, advanced secondary or improved oil recovery techniques (e.g. in"ll drilling and horizontal continuity) and enhanced oil recovery (e.g. CO2 "ooding, steam "ooding, and polymer "ooding) processes are explicitly represented. For natural gas projects, the OLOGSS represents supply from shale formations, tight sands formations, coalbed methane, and other sources.
112 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module Table 9.2. Technically recoverable U.S. natural gas resources as of January 1, 2010 trillion cubic feet Total Technically Proved Unproved Recoverable Reserves Resources Resources Lower 48 Onshore Non Associated Natural Gas 230.0 1250.2 1480.3 Tight Gas 87.9 422.7 510.7 Northeast 5.2 51.8 57.0 Gulf Coast 24.3 96.8 121.1 Midcontinent 7.4 22.1 29.5 Southwest 3.4 24.5 27.9 Rocky Mountain 47.6 222.0 267.6 West Coast 0.0 7.5 7.5 Shale Gas 60.6 481.8 542.3 Northeast 7.1 216.5 223.6 Gulf Coast 10.9 129.7 140.6 Midcontinent 15.4 39.8 55.2 Southwest 26.5 46.1 72.6 Rocky Mountain 0.7 37.4 38.1 West Coast 0.0 12.2 12.2 Coalbed Methane 18.6 122.2 140.8 Northeast 2.5 4.1 6.5 Gulf Coast 1.3 2.2 3.5 Midcontinent 0.7 38.3 38.9 Southwest 0.5 5.8 6.2 Rocky Mountain 13.6 61.6 75.2 West Coast 0.0 10.3 10.3 Other 63.0 223.5 286.5 Northeast 7.0 29.2 36.2 Gulf Coast 10.9 101.2 112.0 Midcontinent 20.3 26.5 46.8 Southwest 16.9 18.6 35.5 Rocky Mountain 7.3 35.0 42.3 West Coast 0.6 13.1 13.7 Lower 48 Onshore Associated-Dissolved Gas 18.4 146.2 164.6 Northeast 0.4 0.6 0.9 Gulf Coast 1.7 23.9 25.6 Midcontinent 1.7 12.3 14.0 Southwest 8.3 40.4 48.7 Rocky Mountain 4.1 45.9 50.0 West Coast 2.1 23.2 25.3 Lower 48 Offshore 15.0 262.6 277.6 Gulf (currently available) 14.2 218.4 232.5 Eastern/Central Gulf (unavailable until 2022) 0.0 21.5 21.5 Paci"c 0.8 10.4 11.2 Atlantic 0.0 12.4 12.4 Alaska (Onshore and Offshore) 9.1 271.7 280.8 Total U.S. 272.5 1930.7 2203.3 Note: Resources in other areas where drilling is officially prohibited are not included. The estimate of 32.9 trillion cubic feet of natural gas resources in the Northern Atlantic, Northern and Central Paci"c, and within a 50-mile buffer off the Mid and Southern Atlantic OCS is also excluded from the technically recoverable volumes because leasing is not expected in these areas by 2035.
Source: Onshore, State Offshore, and Alaska - U.S. Geological Survey (USGS) with adjustments to tight gas, shale gas, and coalbed methane resources; Federal (Outer Continental Shelf) Offshore - Bureau of Ocean Energy Management (formerly the Minerals Management Service); Proved Reserves - U.S. Energy Information Administration. Table values re"ect removal of intervening reserve additions between the date of the latest available assessment and January 1, 2010.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 113
Oil and Gas Supply Module The OLOGSS evaluates the economics of future crude oil and natural gas exploration and development from the perspective of an operator making an investment decision. An important aspect of the economic calculation concerns the tax treatment.
Tax provisions vary with the type of producer (major, large independent, or small independent). For AEO2012, the economics of potential projects re"ect the tax treatment provided by current laws for large independent producers. Relevant tax provisions are assumed unchanged over the life of the investment. Costs are assumed constant over the investment life but vary across region, fuel, and process type. Operating losses incurred in the initial investment period are carried forward and used against revenues generated by the project in later years.
Table 9.3. U.S. unproved technically recoverable tight oil resources by play - AEO2012 Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (mmb/well) (mmb) 2 West Gulf Austin Chalk 16,078 3 72% 61% 0.13 2,688 2 West Gulf Eagle Ford Shale 3,200 5 100% 54% 0.28 2,461 3 Anadarko Woodford Shale 3,120 6 100% 88% 0.02 393 4 Permian Avalon/Bone Springs Shale 1,313 4 100% 78% 0.39 1,593 4 Permian Spraberry 1,085 6 99% 72% 0.11 510 5 Rocky Mountain Basins Niobrara 20,385 8 97% 80% 0.05 6,500 5 Williston Bakken Shale 6,522 2 77% 97% 0.55 5,372 6 San Joaquin/Los Angeles Monterey/Santos Shale 2,520 12 98% 93% 0.50 13,709 Total 33,226 Source: U.S. Energy Information Administration, Office of Energy Analysis.
Table 9.4. U.S. unproved technically recoverable shale gas resources by play - AEO2012 Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (bcf/well) (bcf) 1 Appalachian Devonian Big Sandy 10,669 6 82% 20% 0.57 6,020 1 Appalachian Devonian Greater Sitstone Area 22,914 6 95% 20% 0.33 8,645 1 Appalachian Devonian Low Thermal Maturity 45,844 6 99% 10% 0.50 13,592 1 Appalachian Marcellus - KY Western 207 5 100% 7% 0.13 11 1 Appalachian Marcellus - MD Foldbelt 435 4 100% 5% 0.21 18 1 Appalachian Marcellus - MD Interior 763 4 100% 37% 0.52 630 1 Appalachian Marcellus - NY Interior 10,381 4 100% 37% 2.43 40,123 1 Appalachian Marcellus - NY Western 7,985 5 100% 7% 0.13 425 1 Appalachian Marcellus - OH Interior 361 4 99% 37% 0.52 296 1 Appalachian Marcellus - OH Western 13,515 5 100% 7% 0.13 720 1 Appalachian Marcellus - PA Foldbelt 7,951 4 100% 5% 0.21 323 1 Appalachian Marcellus - PA Interior 23,346 4 98% 37% 2.43 88,180 1 Appalachian Marcellus - PA Western 6,582 5 100% 7% 0.13 351 1 Appalachian Marcellus - TN Foldbelt 353 4 100% 5% 0.21 14 1 Appalachian Marcellus - VA Foldbelt 7,492 4 100% 5% 0.21 304 1 Appalachian Marcellus - VA Interior 321 4 100% 37% 0.52 265 1 Appalachian Marcellus - VA Western 653 5 100% 7% 0.13 35 1 Appalachian Marcellus - WV Foldbelt 2,833 4 100% 5% 0.21 115 1 Appalachian Marcellus - WV Interior 9,989 4 99% 37% 0.52 8,186 1 Appalachian Marcellus - WV Western 10,901 5 98% 7% 0.13 571 1 Appalachian Northwestern Ohio 6,000 4 100% 50% 0.22 2,643 1 Appalachian Utica 16,590 4 100% 21% 1.13 15,712 1 Illinois New Albany 1,600 8 99% 50% 1.72 10,904 1 Michigan Antrim 12,000 8 91% 60% 0.35 18,411 2 Black Warrior Floyd-Neal/Conasauga 2,429 2 100% 65% 1.52 4,805 2 TX-LA-MS Salt Haynesville - LA 3,730 8 96% 49% 3.28 46,102 2 TX-LA-MS Salt Haynesville - TX 5,590 8 99% 24% 1.87 19,758 2 West Gulf Coast Eagle Ford - Dry 2,200 6 99% 43% 1.78 10,044 2 West Gulf Coast Eagle Ford - Wet 5,400 6 99% 49% 2.57 40,175 2 West Gulf Coast Pearsall 1,420 6 100% 85% 1.22 8,817 114 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module Table 9.4. U.S. unproved technically recoverable shale gas resources by play - AEO2012 (cont.)
Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (bcf/well) (bcf) 3 Anadarko Woodford 3,350 4 99% 29% 2.89 10,981 3 Arkoma Caney 2,890 4 100% 29% 0.34 1,135 3 Arkoma Chattanooga 696 8 100% 29% 0.99 1,617 3 Arkoma Fayetteville - Central 3,451 8 88% 22% 1.71 9,070 3 Arkoma Fayetteville - West 2,402 8 100% 25% 0.86 4,170 3 Arkoma Woodford - Western Arkoma 3,000 8 98% 23% 1.97 10,678 3 Southwestern OK Woodford 1,200 4 99% 20% 2.31 2,189 4 Fort Worth Barnett 6,458 8 71% 30% 1.69 18,651 4 Permian Barnett-Woodford 2,691 4 99% 95% 2.70 27,470 5 Greater Green River Hilliard-Baxter-Mancos 17,911 8 100% 25% 0.37 13,285 5 San Juan Lewis 1,557 3 100% 95% 2.20 9,760 5 Uinta Mancos 3,880 8 99% 40% 0.88 10,873 5 Williston Gammon 4,207 2 100% 91% 0.46 3,491 6 Columbia Basin-Centered 6,387 8 100% 17% 1.40 12,220 Total 481,783 Source: U.S. Energy Information Administration, Office of Energy Analysis.
Table 9.5. U.S. unproved technically recoverable tight gas resources by play - AEO2012 Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (bcf/well) (bcf) 1 Appalachian Berea Sandstone 51,863 8 86% 18% 0.18 11,401 1 Appalachian Clinton/Medina High 14,773 8 81% 28% 0.25 6,786 1 Appalachian Clinton/Medina Moderate/Low 27,281 15 86% 59% 0.08 16,136 1 Appalachian Tuscarora Sandstone 42,495 8 100% 1% 0.69 1,485 1 Appalachian Upper Devonian High 12,775 10 58% 67% 0.21 10,493 1 Appalachian Upper Devonian Moderate/Low 29,808 10 82% 37% 0.06 5,492 2 East Texas Cotton Valley/Bossier 14,794 12 96% 29% 1.39 69,720 2 Texas-Gulf Olmos 8,233 4 97% 56% 0.44 7,809 2 Texas-Gulf Vicksburg 3,667 8 93% 11% 2.36 6,929 2 Texas-Gulf Wilcox/Lobo 2,982 8 79% 41% 1.60 12,373 3 Anadarko Cherokee/Redfork 1,978 4 58% 30% 0.90 1,220 3 Anadarko Cleveland 2,562 4 88% 45% 0.91 3,724 3 Anadarko Granite Wash/Atoka 7,790 4 98% 28% 1.72 14,821 3 Arkoma Arkoma Basin 1,000 8 69% 32% 1.30 2,315 4 Permian Abo 1,578 8 91% 99% 1.00 11,386 4 Permian Canyon 6,602 8 91% 85% 0.22 13,105 5 Denver Denver/Jules 4,500 16 88% 86% 0.24 13,212 5 Greater Green River Deep Mesaverde 16,416 4 100% 11% 0.41 2,939 5 Greater Green River Fort Union/Fox Hills 3,858 8 100% 5% 0.70 1,059 5 Greater Green River Frontier (Deep) 15,619 4 100% 7% 2.58 10,801 5 Greater Green River Frontier (Moxa Arch) 2,334 8 89% 16% 1.20 3,076 5 Greater Green River Lance 5,500 8 100% 9% 6.60 24,951 5 Greater Green River Lewis 5,172 8 99% 37% 1.32 19,813 5 Greater Green River Shallow Mesaverde (1) 5,239 4 95% 50% 1.25 12,457 5 Greater Green River Shallow Mesaverde (2) 6,814 8 100% 49% 0.67 17,874 5 Piceance Iles/Mesaverde 1,172 8 99% 94% 0.73 6,379 5 Piceance North Basin Williams Fork/Mesaverde 908 8 100% 90% 0.65 4,278 5 Piceance South Basin Williams Fork/Mesaverde 908 32 99% 84% 0.65 15,648 5 San Juan Central Basin/Dakota 3,918 8 88% 99% 0.98 26,663 5 San Juan Central Basin/Mesaverde 3,689 8 83% 47% 0.82 9,483 5 San Juan Picture Cliffs 6,558 4 63% 1% 0.48 36 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 115
Oil and Gas Supply Module Table 9.5. U.S. unproved technically recoverable tight gas resources by play - AEO2012 (cont.)
Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (bcf/well) (bcf) 5 Uinta Basin Flank Mesaverde 1,708 8 100% 43% 0.99 5,767 5 Uinta Deep Synclinal Mesaverde 2,893 8 100% 14% 0.99 3,292 5 Uinta Tertiary East 1,600 16 96% 33% 0.58 4,690 5 Uinta Tertiary West 1,603 8 100% 21% 4.06 10,914 5 Williston High Potential 2,000 4 77% 89% 0.61 3,343 5 Williston Low Potential 3,000 4 99% 75% 0.21 1,886 5 Williston Moderate Potential 2,000 4 98% 79% 0.33 2,071 5 Wind River Fort Union/Lance Deep 2,500 4 100% 80% 0.54 4,261 5 Wind River Fort Union/Lance Shallow 1,500 8 100% 95% 1.17 13,197 5 Wind River Mesaverde/Frontier Deep 250 4 98% 45% 1.99 876 5 Wind River Mesaverde/Frontier Shallow 250 4 91% 92% 1.25 1,037 6 Columbia Basin-Centered 1,500 8 100% 50% 1.26 7,521 Total 422,719 Source: U.S. Energy Information Administration, Office of Energy Analysis.
Table 9.6. U.S. unproved technically recoverable coalbed methane resources by play - AEO2012 Average Well % of Area Spacing % of Area Area with Average EUR TRR Region Basin Play (mi2) (wells/mi2) Untested Potential (bcf/well) (bcf) 1 Appalachian Central Basin 3,870 8 98% 34% 0.18 1,835 1 Appalachian North Appalachian Basin - High 3,817 12 100% 9% 0.12 536 1 Appalachian North Appalachian Basin - Mod/Low 8,906 12 100% 5% 0.08 469 1 Illinois Central Basin 1,714 8 100% 75% 0.12 1,224 2 Black Warrior Extention Area 700 8 100% 21% 0.08 94 2 Black Warrior Main Area 1,000 12 71% 97% 0.21 1,706 2 Cahaba Cahaba Coal Field 387 8 93% 73% 0.18 379 3 Midcontinent Arkoma 2,998 8 98% 93% 0.22 4,692 3 Midcontinent Cherokee 3,550 8 100% 97% 0.06 1,784 3 Midcontinent Forest City 36,917 8 100% 63% 0.17 31,781 4 Raton Southern 2,028 8 100% 95% 0.37 5,770 5 Greater Green River Deep 3,600 4 100% 45% 0.60 3,879 5 Greater Green River Shallow 720 8 100% 90% 0.20 1,053 5 Greater Green River Western Wyoming 15,097 2 100% 52% 0.46 7,131 5 Piceance Deep 2,000 4 100% 77% 0.60 3,677 5 Piceance Divide Creek 144 8 99% 95% 0.18 194 5 Piceance Shallow 2,000 4 99% 94% 0.30 2,230 5 Piceance White River Dome 216 8 99% 94% 0.41 657 5 Powder River Big George/Lower Fort Union 2,880 16 100% 55% 0.26 6,507 5 Powder River Wasatch 216 8 100% 95% 0.06 92 5 Powder River Wyodak/Upper Fort Union 6,600 20 99% 94% 0.14 16,725 5 Raton Northern 470 8 100% 73% 0.35 957 5 Raton Purgatoire River 360 8 97% 50% 0.31 430 5 San Juan Fairway NM 670 4 84% 30% 1.14 774 5 San Juan North Basin 2,060 4 84% 78% 0.28 1,511 5 San Juan North Basin CO 1,980 4 86% 98% 1.51 10,123 5 San Juan South Basin 1,190 4 94% 92% 0.20 820 5 San Juan South Menefee NM 7,454 5 100% 5% 0.10 177 5 Uinta Blackhaw 1,186 8 100% 97% 0.16 1,423 5 Uinta Ferron 400 8 97% 59% 0.78 1,409 5 Uinta Sego 534 4 100% 64% 0.31 417 5 Wind River Mesaverde 3,018 2 100% 13% 1.73 1,387 6 Western Washington Bellinham/Western Cascade/ 3,655 5 100% 60% 0.94 10,339 Total 122,183 Source: U.S. Energy Information Administration, Office of Energy Analysis.
116 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module Technology Technology advances, including improved drilling and completion practices, as well as advanced production and processing operations, are explicitly modeled to determine the direct impacts on supply, reserves, and various economic parameters. The success of the technology program is measured by estimating the probability that the technology development program will be successfully completed. It re"ects the pace at which technology performance improves and the probability that the technology project will meet the program goals. There are four possible curves which represent the adoption of the technology: convex, concave, sigmoid/logistic and linear. The convex curve corresponds to rapid initial market penetration followed by slow market penetration. The concave curve corresponds to slow initial market penetration followed by rapid market penetration. The sigmoid/logistic curve represents a slow initial adoption rate followed by rapid increase in adoption and then slow adoption again as the market becomes saturated. The linear curve represents a constant rate of market penetration, and may be used when no other predictions can be made.
The market penetration curve is a function of the relative economic attractiveness of the technology instead of being a time-dependent function. A technology will not be implemented unless the bene"ts through increased production or cost reductions are greater than the cost to apply the technology. As a result, the market penetration curve provides a limiting value on commercialization instead of a speci"c penetration path. In addition to the curve, the implementation probability captures the fact that not all technologies that have been proven in the lab are able to be successfully implemented in the "eld. The speci"c technology levers and assumptions are shown in Table 9.7.
Table 9.7. Onshore lower 48 technology assumptions Ultimate Market Probability of Drilling Exploration Estimated Market Penetration Successful Probability of Success Sucess Injection Ultimate Penetration Curve R&D Implementation Rate Rate Rate Recovery Conventional Oil In"ll Drilling 0.59 linear 0.5 0.44 0.03 0.03 -- 0.01 Horizonal Continuity 0.6 linear 0.51 0.44 0.03 0.03 0.25 0.023 Horizontal Pro"le 0.6 concave 0.49 0.45 0.03 0.03 0.02 0.005 CO2 Flooding 0.61 linear 0.51 0.43 0.03 0.03 0.38 0.042 Steam Flooding 0.6 logistic 0.49 0.44 0.03 0.03 0.01 0.09 Polymer Flooding 0.61 concave 0.5 0.44 0.03 0.03 0.123 0.06 Pro"le Modi"cation 0.59 concave 0.51 0.42 0.03 0.03 -- 0.06 Undiscovered 0.6 concave 0.48 0.44 0.03 0.03 -- 0.08 Tight Oil 0.6 concave 0.48 0.44 0.03 0.03 -- 0.08 Conventional Gas Developing 0.61 linear 0.48 0.46 0.03 0.03 -- 0.04 Undiscovered 0.61 linear 0.49 0.45 0.03 0.03 -- 0.07 Tight Gas Developing 0.61 linear 0.48 0.46 0.03 0.03 -- 0.04 Undiscovered 0.61 linear 0.49 0.45 0.03 0.03 -- 0.05 Shale Gas Developing 0.61 linear 0.48 0.45 0.03 0.03 -- 0.08 Undiscovered 0.61 linear 0.48 0.45 0.03 0.03 -- 0.7 Coalbed Methane Developing 0.6 linear 0.5 0.44 0.03 0.03 -- 0.05 Undiscovered 0.6 linear 0.49 0.43 0.03 0.03 -- 0.05 Source: U.S. Energy Information Administration, Office of Energy Analysis.
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Oil and Gas Supply Module CO2 enhanced oil recovery For CO2 miscible "ooding, the OLOGSS incorporates both industrial and natural sources of CO2. The industrial sources of CO2 are:
t Hydrogen plants t Ammonia plants t Ethanol plants t Cement plants t Re"neries (hydrogen) t Fossil fuel power plants t Natural gas processing t Coal/biomass to liquids (CBTL)
Technology and market constraints prevent the total volumes of CO2 (Table 9.8) from becoming immediately available. The development of the CO2 market is divided into 2 periods: 1) development phase and 2) market acceptance phase. During the development phase, the required capture equipment is developed, pipelines and compressors are constructed, and no CO2 is available. During the market acceptance phase, the capture technology is being widely implemented and volumes of CO2 "rst become available. The number of years in each development period is shown in Table 9.9. CO2 is available from planned Carbon Sequestion and Storage (CCS) power plants funded by American Recovery and Reinvestment Act of 2009 (ARRA) starting in 2016.
Table 9.8. Maximum volume of CO2 available billion cubic feet Re"neries Power Natural Gas OGSM Region Natural Hydrogen Ammonia Ethanol Cement (hydrogen) Plants Processing East Coast 0 3 0 52 94 17 12980 23 Gulf Coast 292 0 78 0 86 114 3930 114 Midcontinent 16 0 0 175 48 1 752 0 Southwest 657 0 0 68 74 0 0 0 Rocky Mountains 80 0 3 23 35 62 2907 12 West Coast 0 0 0 4 48 93 1134 40 Northern Great Plains 0 0 0 9 3 16 60 6 Source: U.S. Energy Information Administration. Office of Energy Analysis.
Table 9.9. CO2 availability assumptions Market Development Phase Acceptance Phase Ultimate Market Source Type (years) (years) Acceptance Natural 1 10 100%
Hydrogen 4 10 100%
Ammonia 2 10 100%
Ethanol 4 10 100%
Cement 7 10 100%
Re"neries (hydrogen) 4 10 100%
Power Plants 12 10 100%
Natural Gas Processing 2 10 100%
Source: U.S. Energy Information Administration. Office of Energy Analysis.
118 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module The cost of CO2 from natural sources is a function of the oil price. For industrial sources of CO2, the cost to the producer includes the cost to capture, compress to pipeline pressure, and transport to the project site via pipeline within the region (Table 9.10).
Inter-regional transportation costs add $0.40 per Mcf for every region crossed.
Table 9.10. Industrial CO2 capture & transportation costs by region
$/Mcf Re"neries Natural Gas OGSM Region Hydrogen Ammonia Ethanol Cement (hydrogen) Power Plants Processing CBTL East Coast $2.44 $2.10 $2.23 $4.29 $2.44 $5.96 $1.92 $1.91 Gulf Coast $1.94 $2.10 $2.23 $4.29 $1.94 $5.96 $1.92 $1.91 Midcontinent $2.07 $2.10 $2.23 $4.29 $2.07 $5.96 $1.92 $1.91 Southwest $2.02 $2.10 $2.23 $4.29 $2.02 $5.96 $1.92 $1.91 Rocky Mountains $2.03 $2.10 $2.23 $4.29 $2.03 $5.96 $1.92 $1.91 West Coast $2.01 $2.10 $2.23 $4.29 $2.01 $5.96 $1.92 $1.91 Northern Great Plains $2.05 $2.10 $2.23 $4.29 $2.05 $5.96 $1.92 $1.91 Source: U.S. Energy Information Administration, Office of Energy Analysis.
Lower 48 offshore Most of the Lower 48 offshore oil and gas production comes from the deepwater of the Gulf of Mexico (GOM). Production from currently producing "elds and industry-announced discoveries largely determines the short-term oil and natural gas production projection.
For currently producing "elds, a 20-percent exponential decline is assumed for production except for natural gas production from "elds in shallow water, which uses a 30-percent exponential decline. Fields that began production after 2008 are assumed to remain at their peak production level for 2 years before declining.
The assumed "eld size and year of initial production of the major announced deepwater discoveries that were not brought into production by 2011 are shown in Table 9.11. A "eld that is announced as an oil "eld is assumed to be 100 percent oil and a "eld that is announced as a gas "eld is assumed to be 100 percent gas. If a "eld is expected to produce both oil and gas, 70 percent is assumed to be oil and 30 percent is assumed to be gas.
Production is assumed to:
t ramp up to a peak level in 2 to 4 years depending on the size of the "eld, t remain at the peak level until the ratio of cumulative production to initial resource reaches 20 percent for oil and 30 percent for natural gas, t and then decline at an exponential rate of 20-30 percent.
The discovery of new "elds (based on BOEMS "eld size distribution) is assumed to follow historical patterns. Production from these "elds is assumed to follow the same pro"le as the announced discoveries (as described in the previous paragraph).
Advances in technology for the various activities associated with crude oil and natural gas exploration, development, and production can have a profound impact on the costs associated with these activities. The speci"c technology levers and values for the offshore are presented in Table 9.12.
Leasing is assumed to be available in 2018 in the Mid and South Atlantic, in 2023 in the South Paci"c, and after 2035 in the North Atlantic, Florida straits, Paci"c Northwest, and North and Central California.
Alaska crude oil production Projected Alaska oil production includes both existing producing "elds and undiscovered "elds that are expected to exist, based upon the regions geology. The existing "elds category includes the expansion "elds around the Prudhoe Bay and Alpine Fields for which companies have already announced development schedules. Projected North Slope oil production also includes the initiation of oil production in the Point Thomson Field in 2016. Alaska crude oil production from the undiscovered "elds is determined by the estimates of available resources in undeveloped areas and the net present value of the cash "ow calculated for these undiscovered "elds based on the expected capital and operating costs, and on the projected prices.
The discovery of new Alaskan oil "elds is determined by the number of new wildcat exploration wells drilled each year and by the average wildcat success rate. The North Slope and South-Central wildcat well success rates are based on the success rates reported to the Alaska Oil and Gas Conservation Commission for the period of 1977 through 2008.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 119
Oil and Gas Supply Module Table 9.11. Assumed size and initial production year of major announced deepwater discoveries Field/Project Water Depth Year of Field Size Field Size Start Year of Name Block (feet) Discovery Class (MMBoe) Production Pyrenees GB293 2100 2009 12 89 2012 Wide Berth GC490 3700 2009 12 89 2012 West Tonga GC726 4674 2007 12 89 2012 Bushwood GB463 2700 2009 13 182 2012 Mandy MC199 2478 2010 13 182 2012 Cascade WR206 8143 2002 14 372 2012 Chinook WR469 8831 2003 14 372 2012 Axe DC004 5831 2010 12 89 2013 Dalmatian DC048 5876 2008 12 89 2013 Big Foot WR029 5235 2005 12 89 2013 Knotty Head GC512 3557 2005 14 372 2013 Tubular Bells MC725 4334 2003 12 89 2014 Lucius KC875 7168 2009 13 182 2014 St. Malo WR678 7036 2003 14 372 2014 Jack WR759 6963 2004 14 372 2014 Samurai GC432 3400 2009 12 89 2015 Heidelberg GC859 5000 2009 13 182 2015 Kodiak MC771 4986 2008 13 182 2015 Pony GC468 3497 2006 14 372 2015 Freedom MC948 6095 2008 15 691 2015 Stones WR508 9556 2005 12 89 2016 Mission Deep GC955 7300 1999 13 182 2016 Vito MC984 4038 2009 13 182 2016 Tiber KC102 4132 2009 15 691 2016 Kaskida KC292 5860 2006 15 691 2016 Shenandoah WR052 5750 2009 13 182 2017 Julia WR627 7087 2007 12 89 2018 Buckskin KC872 6920 2009 13 182 2018 Hadrian South KC964 7586 2009 13 182 2019 Appomattox MC392 7217 2009 15 691 2019 Cardamom GB427 2720 2010 13 182 2020 Hadrian North KC919 7000 2010 14 372 2020 Source: U.S. Energy Information Administration, Office of Energy Analysis.
New wildcat exploration drilling rates are determined differently for the North Slope and South-Central Alaska. North Slope wildcat well drilling rates were found to be reasonably well correlated with prevailing West Texas Intermediate crude oil prices.
Consequently, an ordinary least squares statistical regression was employed to develop an equation that speci"es North Slope wildcat exploration well drilling rates as a function of prevailing West Texas Intermediate crude oil prices. In contrast, South-Central wildcat well drilling rates were found to be uncorrelated to crude oil prices or any other criterion. However, South-Central wildcat well drilling rates on average equaled just over 3 wells per year during the 1977 through 2008 period, so 3 South-Central wildcat exploration wells are assumed to be drilled every year in the future.
120 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module Table 9.12. Offshore exploration and production technology levels Total Improvement Technology Level (percent) Number of Years Exploration success rates 30 30 Delay to commence "rst exploration and between 15 30 Exploration & development drilling costs 30 30 Operating cost 30 30 Time to construct production facility 15 30 Production facility construction costs 30 30 Initial constant production rate 15 30 Decline rate 0 30 Source: U.S. Energy Information Administration, Office of Energy Analysis.
On the North Slope, the proportion of wildcat exploration wells drilled onshore relative to those drilled offshore is assumed to change over time. Initially, only a small proportion of all the North Slope wildcat exploration wells are drilled offshore. However, over time, the offshore proportion increases linearly, so that after 20 years, 50 percent of the North Slope wildcat wells are drilled onshore and 50 percent are drilled offshore. The 50/50 onshore/offshore wildcat well apportionment remains constant through the remainder of the forecast in recognition of the fact that offshore North Slope wells and "elds are considerably more expensive to drill and develop, thereby providing an incentive to continue drilling onshore wildcat wells even though the expected onshore "eld size is considerably smaller than the oil "elds expected to be discovered offshore.
The size of the new oil "elds discovered by wildcat exploration drilling is based on the expected "eld sizes of the undiscovered Alaska oil resource base, as determined by the U.S. Geological Survey for the onshore and State offshore regions of Alaska, and by the Bureau of Ocean Energy Management (BOEM) (formerly known as the U.S. Minerals Management Service) for the Federal offshore regions of Alaska. It is assumed that the largest undiscovered oil "elds will be found and developed "rst and in preference to the small and midsize undiscovered "elds. As the exploration and discovery process proceeds and as the largest oil "elds are discovered and developed, the discovery and development process proceeds to "nd and develop the next largest set of oil "elds. This large to small discovery and development process is predicated on the fact that developing new infrastructure in Alaska, particularly on the North Slope, is an expensive undertaking and that the largest "elds enjoy economies of scale, which make them more pro"table and less risky to develop than the smaller "elds.
Oil and gas exploration and production currently are not permitted in the Arctic National Wildlife Refuge. The projections for Alaska oil and gas production assume that this prohibition remains in effect throughout the projection period.
Three uncertainties are associated with the Alaska oil projections. First, whether the heavy oil deposits located on the North Slope, which exceed 20 billion barrels of oil-in-place, will be producible in the foreseeable future at recovery rates exceeding a few percent. Second, the oil production potential of the North Slope shale formations is unknown at this time. Third, the North Slope offshore oil resource potential, especially in the Chukchi Sea, is untested.
In June 2011, Alyeska Pipeline Service Company released a report regarding potential operational problems that might occur as Trans-Alaska Pipeline System (TAPS) throughput declines from the current production levels.[6] Although the onset of TAPS low "ow problems could begin at around 550,000 barrels per day, absent any mitigation, the severity of the TAPS operational problems is expected to increase signi"cantly as throughput declines. As the types and severity of problems multiplies, the investment required to mitigate those problems is expected to increase signi"cantly. Because of the many and diverse operational problems expected to occur below 350,000 barrels per day of throughput, considerable investment might be required to keep the pipeline operational below this threshold. For the Annual Energy Outlook 2012 projections, an algorthim was installed into the Alaska Oil & Gas Supply Submodule that assumed that North Slope "elds would be shut down, plugged, and abandoned when the following 2 conditions are simultaneously satis"ed: 1) TAPS throughput would have to be at or below 350,000 barrels per day and
- 2) total North Slope oil production revenues would have to be at or below $5.0 billion per year. The Annual Energy Outlook 2012 Issues in Focus article, entitled: The Potential Shutdown of Alaska North Slope Oil Production, discusses these assumptions and their rationale.
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Oil and Gas Supply Module Legislation and regulations The Outer Continental Shelf Deep Water Royalty Act (Public Law 104-58) gave the Secretary of the Interior the authority to suspend royalty requirements on new production from qualifying leases and required that royalty payments be waived automatically on new leases sold in the 5 years following its November 28, 1995 enactment. The volume of production on which no royalties were due for the 5 years was assumed to be 17.5 million barrels of oil equivalent (BOE) in water depths of 200 to 400 meters, 52.5 million BOE in water depths of 400 to 800 meters, and 87.5 million BOE in water depths greater than 800 meters. In any year during which the arithmetic average of the closing prices on the New York Mercantile Exchange for light sweet crude oil exceeded $28 per barrel or for natural gas exceeded $3.50 per million Btu, any production of crude oil or natural gas was subject to royalties at the lease-stipulated royalty rate. Although automatic relief expired on November 28, 2000, the act provided the Minerals Management Service (MMS) the authority to include royalty suspensions as a feature of leases sold in the future. In September 2000, the MMS issued a set of proposed rules and regulations that provide a framework for continuing deep water royalty relief on a lease-by-lease basis. In the model it is assumed that relief will be granted at roughly the same levels as provided during the "rst 5 years of the act.
Section 345 of the Energy Policy Act of 2005 provides royalty relief for oil and gas production in water depths greater than 400 meters in the Gulf of Mexico from any oil or gas lease sale occurring within 5 years after enactment. The minimum volumes of production with suspended royalty payments are:
(1) 5,000,000 barrels of oil equivalent (BOE) for each lease in water depths of 400 to 800 meters; (2) 9,000,000 BOE for each lease in water depths of 800 to 1,600 meters; (3)12,000,000 BOE for each lease in water depths of 1,600 to 2,000 meters; and (4) 16,000,000 BOE for each lease in water depths greater than 2,000 meters.
The water depth categories speci"ed in Section 345 were adjusted to be consistent with the depth categories in the Offshore Oil and Gas Supply Submodule. The suspension volumes are 5,000,000 BOE for leases in water depths of 400 to 800 meters; 9,000,000 BOE for leases in water depths of 800 to 1,600 meters; 12,000,000 BOE for leases in water depths of 1,600 to 2,400 meters; and 16,000,000 for leases in water depths greater than 2,400 meters. Examination of the resources available at 2,000 to 2,400 meters showed that the differences between the depths used in the model and those speci"ed in the bill would not materially affect the model result.
The MMS published its "nal rule on the Oil and Gas and Sulphur Operations in the Outer Continental Shelf Relief or Reduction in Royalty Rates Deep Gas Provisions on January 26, 2004, effective March 1, 2004. The rule grants royalty relief for natural gas production from wells drilled to 15,000 feet or deeper on leases issued before January 1, 2001, in the shallow waters (less than 200 meters) of the Gulf of Mexico. Production of gas from the completed deep well must begin before 5 years after the effective date of the "nal rule. The minimum volume of production with suspended royalty payments is 15 billion cubic feet for wells drilled to at least 15,000 feet and 25 billion cubic feet for wells drilled to more than 18,000 feet. In addition, unsuccessful wells drilled to a depth of at least 18,000 feet would receive a royalty credit for 5 billion cubic feet of natural gas. The ruling also grants royalty suspension for volumes of not less than 35 billion cubic feet from ultra-deep wells on leases issued before January 1, 2001.
Section 354 of the Energy Policy Act of 2005 established a competitive program to provide grants for cost-shared projects to enhance oil and natural gas recovery through CO2 injection, while at the same time sequestering CO2 produced from the combustion of fossil fuels in power plants and large industrial processes.
From 1982 through 2008, Congress did not appropriate funds needed by the MMS to conduct leasing activities on portions of the Federal Outer Continental Shelf (OCS) and thus effectively prohibited leasing. Further, a separate Executive ban in effect since 1990 prohibited leasing through 2012 on the OCS, with the exception of the Western Gulf of Mexico and portions of the Central and Eastern Gulf of Mexico. When combined, these actions prohibited drilling in most offshore regions, including areas along the Atlantic and Paci"c coasts, the eastern Gulf of Mexico, and portions of the central Gulf of Mexico. In 2006, the Gulf of Mexico Energy Security Act imposed yet a third ban on drilling through 2022 on tracts in the Eastern Gulf of Mexico that are within 125 miles of Florida, east of a dividing line known as the Military Mission Line, and in the Central Gulf of Mexico within 100 miles of Florida.
On July 14, 2008, President Bush lifted the Executive ban and urged Congress to remove the Congressional ban. On September 30, 2008, Congress allowed the Congressional ban to expire. Although the ban through 2022 on areas in the Eastern and Central Gulf of Mexico remains in place, the lifting of the Executive and Congressional bans removed regulatory obstacles to development of the Atlantic and Paci"c OCS.
122 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Oil and Gas Supply Module Oil and gas supply alternative cases Tight Oil and Shale Gas Resource cases Estimates of technically recoverable shale gas resources are highly uncertain and change over time as new information is gained through drilling, production, and technology experimentation. Over the last decade, as more shale formations have gone into production, the estimate of technically recoverable shale gas resources has skyrocketed. However, these increases in technically recoverable shale gas resources embody many assumptions that might not prove to be true over the long term and over the entire shale formation. For example, these shale gas resource estimates assume that gas production rates achieved in a limited portion of the formation are representative of the entire formation, even though neighboring shale gas well production rates can vary by as much as a factor of three. Moreover, the shale formation can vary signi"cantly across the petroleum basin with respect to depth, thickness, porosity, carbon content, pore pressure, clay content, thermal maturity, and water content. Three cases were developed to examine the impact of the uncertainty inherent in these resource estimates by adjusting the estimated ultimate recovery (EUR) per well and the well spacing, both key components in the estimation of technically recoverable resources (see Issues in Focus article, U.S. Crude Oil and Natural Gas Resource Uncertainty).
Low EUR case. In this case, the EUR per tight oil and shale gas well is assumed to be 50 percent lower than in the Reference case, increasing the per-unit cost of developing the resource. The total unproved technically recoverable tight oil resource is decreased to 17 billion barrels and the shale gas resource is decreased to 241 trillion cubic feet, compared to 33 billion barrels of tight oil and 482 trillion cubic feet of shale gas assumed in the Reference case.
High EUR case. The EUR per tight oil and shale gas well is assumed to be 50 percent higher than in the Reference case, decreasing the per-unit cost of developing the resource. The total unproved technically recoverable tight oil resource is increased to 50 billion barrels and the shale gas resource is increased to 723 trillion cubic feet.
High TRR case. The well spacing for all tight oil and shale gas plays is assumed to be 8 wells per square mile (i.e., each well has an average drainage area of 80 acres) and the EUR per tight oil and shale gas wells are assumed to be 50 percent higher than in the Reference case. Additionally, production in the short term from the eight tight oil plays was adjusted to re"ect the latest available data. The total unproved technically recoverable tight oil resource is increased to 89 billion barrels and the shale gas resource is increased to 1,091 trillion cubic feet, more than twice the Reference case tight oil and shale gas resource assumptions.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 123
Oil and Gas Supply Module Notes and sources
[1] The current development of tight oil plays has shifted industry focus and investment away from the development of U.S. oil shale (kerogen) resources. Considerable technological development is required prior to the large-scale in-situ production of oil shale being economically feasible. Consequently, the Oil Shale Supply Submodule assumes that large-scale in-situ oil shale production is not commercially feasible prior to 2035.
[2] Technically recoverable resources are resources in accumulations producible using current recovery technology but without reference to economic pro"tability.
[3] Proved reserves are the estimated quantities that analysis of geological and engineering data demonstrate with reasonable certainty to be recoverable in future years from known reservoirs under existing economic and operating conditions.
[4] Unproved resources include resources that have been con"rmed by exploratory drilling and undiscovered resources, which are located outside oil and gas "elds in which the presence of resources has been con"rmed by exploratory drilling; they include resources from undiscovered pools within con"rmed "elds when they occur as unrelated accumulations controlled by distinctly separate structural features or stratigraphic conditions.
[5] Donald L. Gautier and others, U.S. Department of the Interior, U.S. Geological Survey, 1995 National Assessment of the United States Oil and Gas Resources, (Washington, D.C., 1995); U.S. Department of the Interior, Minerals Management Service, Report to Congress: Comprehensive Inventory of U.S. OCS Oil and Natural Gas Resources, (February 2006); and 2003 estimates of conventionally recoverable hydrocarbon resources of the Gulf of Mexico and Atlantic Outer Continental Shelf as of January 1, 2003.
[6] Alyeska Pipeline Service Company, Low Flow Impact Study, Final Report, June 15, 2011, Anchorage, Alaska, at www.alyeska-pipe.com/Inthenews/LowFlow/LoFIS_Summary_Report_P6%2027_FullReport.pdf.
124 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Natural Gas Transmission and Distribution Module
THIS PAGE INTENTIONALLY LEFT BLANK Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and "ows of natural gas through a regional interstate representative pipeline network, for both a peak (December through March) and off-peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. Natural gas "ow patterns are a function of the pattern in the previous year, coupled with the relative prices of the supply options available to bring gas to market centers within each of the NGTDM regions (Figure 9). The major assumptions used within the NGTDM are grouped into four general categories. They relate to (1) structural components of the model, (2) capacity expansion and pricing of transmission and distribution services, (3) Arctic pipelines, and (4) imports and exports. A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2012, DOE/EIA-M062(2012) (Washington, DC, 2012).
Figure 9. Natural Gas Transmission and Distribution Module Regions Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 127
Natural Gas Transmission and Distribution Module Key assumptions Structural components The primary and secondary region-to-region "ows represented in the model are shown in Figure 9. Primary "ows are determined, along with nonassociated gas production levels, as the model equilibrates supply and demand. Associated-dissolved gas production is determined in the Oil and Gas Supply Module (OGSM). Secondary "ows are established before the equilibration process and are generally set exogenously. Lique"ed natural gas (LNG) imports are also not directly part of the equilibration process, but are set at the beginning of each NEMS iteration in response to the price from the previous iteration. LNG exports, both re-exports and domestically sourced volumes, are set exogenously to the model. Flows and production levels are determined for each season, linked by seasonal storage. When required, annual quantities (e.g., consumption levels) are split into peak and off-peak values based on historical averages. When multiple regions are contained in a Census Division, regional end-use consumption levels are approximated using historical average shares. Pipeline and storage capacity are added as warranted by the relative volumes and prices. Regional pipeline fuel and lease and plant fuel consumption are established by applying an historically based factor to the "ow of gas through a region and the production in a region, respectively. Prices within the network, including at the borders and the wellhead, are largely determined during the equilibration process. Delivered prices for each sector are set by adding an endogenously estimated markup (generally a distributor tariff) to the regional representative citygate price. Supply curves and electric generator gas consumption are provided by other NEMS modules for subregions of the NGTDM regions, re"ective of how their internal regions overlap with the NGTDM regions.
Capacity expansion and pricing of transmission and distribution For the "rst two projection years, announced pipeline and storage capacity expansions (that are deemed highly likely to occur) are used to establish limits on "ows and seasonal storage in the model. Subsequently, pipeline and storage capacity is added when increases in consumption, coupled with an anticipated price increase, warrant such additions (i.e., "ow is allowed to exceed current capacity if the demand still exists given an assumed increased tariff). Once it is determined that an expansion will occur, the associated capital costs are applied in the revenue requirement calculations in future years. Capital costs are assumed based on average costs of recent comparable expansions for compressors, looping, and new pipeline.
It is assumed that pipeline and local distribution companies build and subscribe to a portfolio of interstate pipeline and storage capacity to serve a region-speci"c colder-than-normal winter demand level, currently set at 30 percent above the daily average.
Maximum pipeline capacity utilization in the peak period is set at 99 percent. In the off-peak period, the maximum is assumed to vary between 75 and 99 percent of the design capacity. The overall level and pro"le of consumption, as well as the availability and price of supplies, generally cause realized pipeline utilization levels to be lower than the maximum.
Pricing of services While transportation tariffs for interstate pipeline services are initially based on a regulated cost-of-service calculation, an adjustment to the tariffs is applied which is dependent on the realized utilization rate, to re"ect a market-based differential.
Reservation and operation transportation rates for interstate pipeline services (both between NGTDM regions and within a region) are calculated assuming that the costs of new pipeline capacity will be rolled into the existing rate base.
Delivered prices by sector and season are derived by adding a markup to the average regional market price of natural gas in both peak and off-peak periods. (Prices are reported on an annual basis and represent quantity-weighted averages of the two seasons.)
These markups include the cost of service provided by intraregional interstate pipelines, intrastate pipelines, and local distributors.
The intrastate tariffs are accounted for endogenously through historical model benchmarking. Distributor tariffs represent the difference between the regional delivered and citygate price, independent of whether or not a customer class typically purchases gas through a local distributor.
The distribution tariffs are projected using econometrically estimated equations, primarily in response to changes in consumption levels. An assumed differential is used to divide the industrial price into one for non-core customers (re"neries and industrial boiler users) and one for core customers who have fewer alternative fuel options.
The vehicle natural gas (VNG) sector is divided into "eet and non-"eet vehicles. In general, the distributor tariffs for natural gas to vehicles are set to EIAs Natural Gas Annual historical end-use prices minus citygate prices plus Federal and State VNG taxes (held constant in nominal dollars) plus an assumed dispensing cost. Dispensing costs are assumed to be $2.40 (2010 dollars per Mcf) as long as natural gas vehicles do not increase notably in market share. The assumed cost for adding a compressed natural gas retail facility is $406,000 (2010 dollars), after accounting for the tax value of depreciation, and is not considered economically viable at the low vehicle penetration rates projected.
Pipelines from arctic areas into Alberta The outlook for natural gas production from the North Slope of Alaska is affected strongly by the unique circumstances regarding its transport to market. Unlike virtually all other identi"ed deposits of natural gas in the United States, North Slope gas lacks a means of economic transport to major commercial markets. The lack of viable marketing potential at present has led to the use 128 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Natural Gas Transmission and Distribution Module of Prudhoe Bay gas to maximize crude oil recovery in that "eld. The option of exporting North Slope gas as LNG was not included in the model for AEO2012. The primary assumptions associated with estimating the cost of North Slope Alaskan gas in Alberta, as well as for MacKenzie Delta gas into Alberta, are shown in Table 10.1. A calculation is performed to estimate a regulated, levelized tariff for each pipeline. Additional items are added to account for the wellhead price, treatment costs, pipeline fuel costs, and a risk premium to re"ect the potential impact on the market price once the pipeline comes on line.
To assess the market value of Alaskan and Mackenzie Valley gas against the lower 48 market, a price differential of $0.73 (2010 dollars per Mcf) is assumed between the price in Alberta and the average lower 48 wellhead price. The resulting cost of Alaska gas, relative to the lower 48 wellhead price, is approximately $6.10 (2010 dollars per Mcf), with some variation across the projection due to changes in gross domestic product. Construction of an Alaska-to-Alberta pipeline is projected to commence if the assumed total costs for Alaska gas in the lower 48 States exceed the average lower 48 gas price in each of the previous two years, on average over the previous "ve years (with greater weight applied to more recent years), and as expected to average over the next three years. An adjustment is made if prices were declining over the previous "ve years. Once the assumed four-year construction period is complete, expansion can occur if the price exceeds the initial trigger price by $6.72 (2010 dollars per Mcf). Supplies to "ll an expanded pipeline are assumed to require new gas wells. When the Alaska-to-Alberta pipeline is built in the model, additional pipeline capacity is added to bring the gas across the border into the United States. For accounting purposes, the model assumes that all of the Alaska gas will be consumed in the United States and that sufficient economical supplies are available at the North Slope to "ll the pipeline over the depreciation period.
Natural gas production from the Mackenzie Delta is assumed to be sufficient to "ll a pipeline over the projection period should one be built connecting the area to markets in the south. The basic methodology used to represent the decision to build a Mackenzie pipeline is similar to the process used for an Alaska-to-lower 48 pipeline, using the primary assumed parameters listed in Table 10.1. One exception is that wellhead costs are assumed to change across the projection period with estimated changes to drilling costs for the lower 48 States.
Supplemental natural gas The projection for supplemental gas supply is identi"ed for three separate categories: pipeline quality synthetic natural gas (SNG) from coal or coal-to-gas (CTG), SNG from liquids, and other supplemental supplies (propane-air, coke oven gas, re"nery gas, biomass air, air injected for Btu stabilization, and manufactured gas commingled and distributed with natural gas). The third category, other supplemental supplies, are held at a constant level of 12.3 billion cubic feet per year throughout the projection because this level is consistent with historical data and it is not believed to change signi"cantly in the context of a Reference case. SNG from liquid hydrocarbons in Hawaii is assumed to continue over the projection at the average historical level of 2.6 billion cubic feet per year. SNG production from coal at the currently operating Great Plains Coal Gasi"cation Plant is also assumed to continue through the projection period at an average historical level of 52.2 billion cubic feet per year. It is assumed that additional CTG facilities will be built if and when natural gas prices are high enough to make them economic. One CTG facility is assumed capable of processing 6,040 tons of bituminous coal per day, with a production capacity of 0.1 billion cubic feet per day of synthetic fuel and approximately 100 megawatts of capacity for electricity cogeneration sold to the grid. A CTG facility of this size is assumed to cost nearly $1 billion in initial capital investment (2010 dollars). CTG facilities are assumed to be built near existing coal mines. All NGTDM regions are considered potential locations for CTG facilities except for New England.
Synthetic gas products from CTG facilities are assumed to be competitive when natural gas prices rise above the cost of CTG production (adjusted for credits from the sale of cogenerated electricity). It is assumed that CTG facilities will not be built before 2012.
Natural gas imports and exports U.S. natural gas trade with Mexico is determined endogenously based on various assumptions about the natural gas market in Mexico. Natural gas consumption levels in Mexico are set exogenously based on projections from the International Energy Outlook 2010 and are provided in Table 10.2, along with initially assumed Mexico production and LNG import levels targeted for markets in Mexico. Adjustments to production are made endogenously within the model to re"ect a response to price "uctuations within the market. Domestic production is assumed to be supplemented by LNG from receiving terminals constructed on both the east and west coasts of Mexico. Maximum LNG import volumes targeted for markets in Mexico are set exogenously and will be realized if endogenously determined LNG imports into North America are sufficient. The difference between production plus LNG imports and consumption in Mexico in any year is assumed to be either imported from, or exported to, the United States.
Similarly to Mexico, Canada is modeled through a combination of exogenously and endogenously speci"ed components. Natural gas exports from the United States to Canada are set exogenously in NEMS starting at 721 billion cubic feet per year in 2010 and increasing to 1524 billion cubic feet by 2035. Canadian production and U.S. import "ows from Canada are determined endogenously within the model. Canadian natural gas production in Eastern Canada and consumption are set exogenously in the U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 129
Natural Gas Transmission and Distribution Module Table 10.1. Primary assumptions for natural gas pipelines from Alaska and Mackenzie delta into Alberta, Canada Alaska to Alberta Mackenzie Delta to Alberta Initial "ow into Alberta 3.8 billion cubic feet per day 1.1 billion cubic feet per day Expansion potential 22 percent 58 percent Initial capitalization $36.0 billion (2009 dollars) $10.7 billion (2010 dollars)
Cost of Debt (premium over 10-year treasury note yield) 0.75 percent 0.0 percent Cost of equity (premium over 10-year treasury note yield) 6.5 percent 7.5 percent Debt fraction 70 percent 60 percent Depreciation period 20 years 20 years Minimum wellhead price (including treatment and fuel costs) $1.72 (2010 dollars per Mcf) $3.16 (2010 dollars per Mcf)
Expected price reduction $1.01 (2010 dollars per Mcf) $0.06 (2010 dollars per Mcf)
Additional cost for expansion $6.73 (2010 dollars per Mcf)* $0.37 (2010 dollars per Mcf)
Construction period 4 years 4 years Planning period 5 years 2 years Earliest start year 2021 2018
- Includes added cost to explore for and produce natural gas beyond what has already been proven.
Source: U.S. Energy Information Administration, Office of Energy Analysis. Alaska pipeline cost data are based on Federal Energy Regulatory Commission, Docket PF09-11-001, Open Season Plan Documents Submitted in Connection with Request for Commission Approval of Detailed Plan for Conducting an Open Season, submitted by TransCanada Alaska Company LLC on January 29, 2010, Volume III of III, Appendix C, Exhibit J - Recourse Rate Output, various pages.
Note that the capital cost "gure is the arithmetic average of the two $30.7 and $40.4 billion capital cost estimates that include the mainline gas pipeline and the gas treatment plant, but which exclude the gas "eld line from Point Thomson to the gas treatment plant. National Energy Board of Canada, Mackenzie Gas Project - Hearing Order GH-1-2004, Supplemental Information - Project Update 2007, dated May 15, 2007; National Energy Board of Canada, Mackenzie Gas Project - Project Cost Estimate and Schedule Update, dated March 12, 2007; Canada Revenue Agency, T2 Corporation Income Tax Guide 2006, T4012(E)
Rev. 07. Indian and Northern Affairs Canada, Oil and Gas in Canadas North, website address www.ainc-inac.gc.ca/ps/ecd/env/nor_e.html. National Energy Board of Canada, Application for Approval of the Development Plan for Taglu Field - Project Description, submitted by Imperial Oil Resources Ltd., TDPA-P1, August 2004; National Energy Board of Canada, Application for Approval of the Development Plan for Niglintgak Field - Project Description, submitted by Shell Canada Ltd., NDPA-P1, August 2004; and National Energy Board of Canada, Application for Approval of the Development Plan for Parsons Lake Field - Project Description,
+- = 4<= " 6" 4 billion cubic feet per year Consumption Initial Dry Production Initial LNG Imports 2015 2471 1775 3 2020 2987 1592 501 2025 3705 1533 977 2030 4353 1679 1231 2035 5020 1988 1367 Source: Consumption - U.S. Energy Information Administration. International Energy Outlook 2011 DOE/EIA-0484(2011); Production - U.S. Energy Information Administration, Office of Petroleum, Gas, and Biofuels Analysis. LNG imports - U.S. Energy Information Administration, International Energy Outlook 2011, DOE/EIA-0484(2011).
Note: Excludes LNG imported to Mexico for export to the United States.
model and are shown in Table 10.3. Production from conventional and tight formations in the Western Canadian Sedimentary Basin (WCSB) is calculated endogenously to the model using annual supply curves based on beginning-of-year proved reserves and an estimated production-to-reserve ratio. Reserve additions are set equal to the product of successful natural gas wells and a "nding rate (both based on an econometric estimation). The initial coalbed methane, shale gas, and conventional WCSB economically recoverable unproved resource base estimates assumed in the model are 78.4 trillion cubic feet (starting in 2008),
108.0 trillion cubic feet (starting in 2011), and 95.8 trillion cubic feet (starting in 2004), respectively. [1] Potential production from tight formations was approximately by increasing the conventional resource level by 2.3 percent annually. Production from coalbed and shale sources is established based on an assumed production path which varies in response to the level of remaining resources and the solution prce in the previous projection year.
Annual U.S. exports of lique"ed natural gas (LNG) to Japan are assumed to cease in 2011. For AEO2012 potential future LNG exports from Alaska were not modeled. LNG exports of domestially produced natural gas from the lower 48 States are assumed to start during 2016 at 1.1 billion cubic feet per day and double during 2019. LNG re-exports are assumed to stay at 100 billion 130 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Natural Gas Transmission and Distribution Module cubic feet per year throughout the forecast period, close to current historical levels. LNG imports to the United States are determined endogenously within the model. For the most part, LNG imports are set endogenously in the model based on Atlantic/
Paci"c and peak/off-peak supply curves derived from model results generated by EIAs International Natural Gas Model (INGM).
Prices from the previous model iteration are used to establish the total level of North American imports in the peak or off-peak period and in the Atlantic or Paci"c. First, assumed LNG imports which are consumed in Mexico are subtracted (presuming the volumes are sufficient). Then, the remaining levels are allocated to the model regions based on last years import levels, the available regasi"cation capacity, and the relative prices. Regasi"cation capacity is limited to facilities currently in existence and those already under construction, which is fully sufficient to accommodate import levels projected by the model.
+- = 4!" 6" 4 billion cubic feet per year Year Consumption Production Eastern Canada 2010 2,913 119 2015 3,507 98 2020 3,742 78 2025 4,175 61 2030 4,558 48 2035 5,041 38 Source: Consumption - U.S. Energy Information Administration. International Energy Outlook 2011, DOE/EIA-0484(2011); Production - Energy Information Administration, Office of Petroleum, Gas, and Biofuels Analysis.
Legislation and regulations The methodology for setting reservation fees for transportation services is initially based on a regulated rate calculation, but is ultimately consistent with FERCs alternative ratemaking and capacity release position in that it allows some "exibility in the rates pipelines ultimately charge. The methodology is market-based in that rates for transportation services will respond positively to increased demand for services while rates will decline should the demand for services decline.
Section 116 of the Military Construction Appropriations and Emergency Hurricane Supplemental Appropriations Act, 2004 (H.R.4837) gives the Secretary of Energy the authority to issue Federal loan guarantees for an Alaska natural gas transportation project, including the Canadian portion, that would carry natural gas from northern Alaska, through the Canadian border south of 68 degrees north latitude, into Canada, and to the lower 48 States. This authority would expire 2 years after the "nal certi"cate of public convenience and necessity is issued. In aggregate the loan guarantee would not exceed: (1) 80 percent of total capital costs (including interest during construction); (2) $18 billion (indexed for in"ation at the time of enactment); or (3) a term of 30 years.
The Act also promotes streamlined permitting and environmental review, an expedited court review process, and protection of rights-of-way for the pipeline. The assumed costs of borrowing money for the pipeline were reduced to re"ect the decreased risk as a result of the loan guarantee.
Section 706 of the American Jobs Creation Act of 2004 (H.R.4520) provided a 7-year cost-of-investment recovery period for the Alaska natural gas pipeline, as opposed to the previously allowed 15-year recovery period, for tax purposes. The provision is effective for property placed in service after 2013 (or treated as such) and is assumed to have minimal impact on the decision to build the pipeline.
Section 707 of the American Jobs Creation Act extended the 15-percent tax credit previously applied to costs related to enhanced oil recovery to construction costs for a gas treatment plant that supplies natural gas to a 2 trillion Btu per day pipeline, lies in Northern Alaska, and produces carbon dioxide for injection into hydrocarbon-bearing geological formations. A gas treatment plan on the North Slope that feeds gas into an Alaska pipeline to Canada is expected to satisfy this requirement. The provision is effective for costs incurred after 2004. The impact of this tax credit is assumed to be factored into the cost estimates "led by the participating companies.
Section 312 of the Energy Policy Act of 2005 authorizes the Federal Energy Regulatory Commission (FERC) to allow natural gas storage facilities to charge market-based rates if it was believed that they would not exert market power. Storage rates are allowed to vary in the model from regulation-based rates, depending on market conditions.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 131
Natural Gas Transmission and Distribution Module The Heavy-duty vehicles reference and the heavy-duty natural gas vehicle potential cases The HD NGV Potential case permits expansion of the HDV market to allow a gradual increase in the share of HDV owners who would consider purchasing a NGV if justi"ed by the fuel economics over a payback period with a weighted average of 3 years. Details of this case are described in the Transportation Demand Module chapter. In the process of de"ning this case, EIA reexamined and modi"ed the assumptions that were used for the AEO2012 Reference case related to setting the prices for compressed natural gas (CNG) and lique"ed natural gas (LNG) at private refueling stations ("eets) and at public retail stations above the price for the dry natural gas itself. The HDV Reference case was developed using these updated assumptions in order to provide a consistent basis for comparison with the HD HGV Potential case. The same assumptions, as described below, are used for setting these prices in both the HD NGV Potential case and the HDV Reference case.
The distributor markup for natural gas delivered via pipeline to a CNG station is based off historical data for the sector. A retail markup and motor fuel (excise) taxes are added to set the "nal retail price. The excise taxes applied and the value and assumptions behind the retail markups assumed are shown in Table 10.4. The price for delivered dry natural gas to a liquefaction plant is approximated by using the price to electric generators. The price for LNG is therefore set to the price to electric generators, plus the assumed price to liquefy and transport the LNG, the retail price markup at the station, and the excise taxes.
The values for these components and the primary assumptions behind them are shown in Table 10.4. The table shows the national average State excise tax, while in the model these taxes vary by region.
Table 10.4. Assumptions related to CNG and LNG fuel prices Year CNG CNG LNG LNG "eet retail "eet retail Retail markup after dry gas pipeline delivery, with no excise tax (2010$/dge) 0.80 0.93 1.39 1.58 Capacity (dge/day) 1600 1100 4000 4000 Usage (percent of capacity) 80 0 80 0 Capital cost (million 2010$) 0.8 0.5 1.0 1.0 Capital recovery (years) 5 10 5 10 Weighted average cost of capital (rate) 0.10 0.15 0.10 0.15 Operating cost (2010$/dge) 0.34 0.51 0.41 0.59 Charge for liquefying an ddelivering LNG (2010$/dge -- -- 0.75 0.75 Federal excise tax (nominal$/dge) 0.21 0.21 0.42 0.42 State excise tax (nominal$/dge) 0.15 0.15 0.24 0.24 Fuel loss for liquefying and delivering LNG (percent of input volumes) -- -- 10 10 Fuel loss at station (percent of input volumes) 0. 0.5 1.0 2.0 Source: U.S. Energy Information Administration, U.S. Tax Code and State Tax Codes.
Note: dge is diesel-gallon equivalent.
Notes and sources
[1] Coalbed, shale gas, and tight sands unproved resource based on assumptions used in EIAs International Natural Gas Model for the International Energy Outlook 2011.
132 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
THIS PAGE INTENTIONALLY LEFT BLANK Petroleum Market Module THIS PAGE INTENTIONALLY LEFT BLANK Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, un"nished oil imports, other re"nery inputs (including alcohols, ethers, esters, corn, biomass, and coal), natural gas plant liquids production, and re"nery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic re"neries.
The PMM contains a linear programming (LP) representation of U.S. re"ning activities in the "ve Petroleum Administration for Defense Districts (PADDs) (Figure 10), linked to a simpli"ed world re"ning industry representation used to model U.S. crude and product imports. The U.S. segment of the LP model is created by aggregating individual U.S. re"neries within a PADD into two types of representative re"neries and linking all "ve PADDs and world re"ning regions via crude and product transit links.
This representation provides the marginal costs of production for a number of conventional and new petroleum products.
In order to interact with other NEMS modules with different regional representations, certain PMM inputs and outputs are converted from PADD regions to other regional structures and vice versa. The linear programming results are used to determine end-use product prices for each Census Division (shown in Figure 5) using the assumptions and methods described below.
Figure 10. Petroleum Administration for Defense Districts Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 135
Petroleum Market Module Key assumptions Product types and speci"cations The PMM models re"nery production of the products shown in Table 11.1.
The costs of producing different formulations of gasoline and diesel fuel that are required by State and Federal regulations are determined within the linear programming (LP) representation of re"neries by incorporating the speci"cations and demands for these fuels. The PMM assumes that the speci"cations for these fuels will remain the same as currently speci"ed, with a few exceptions: sulfur content, which is phased down to re"ect EPA regulations for all gasoline and diesel fuels; and benzene content, which was reduced in gasoline in 2011.
Table 11.1. Petroleum product categories Product Category Speci"c Products Motor Gasoline Conventional, Reformulated Jet Fuel Kerosene-type Distillates Kerosene, Heating Oil, Low-Sulfur, Ultra-Low-Sulfur and CARB Diesel Residual Fuels Low Sulfur, High Sulfur Lique"ed Petroleum Gases
Petrochemical Feedstock
! " #& '
Others + :' ;
Source: U.S. Energy Information Administration, Office of Energy Analysis.
Motor gasoline speci"cations and market shares The PMM models the production and distribution of two different types of gasoline: conventional and reformulated (Phase 2). The following speci"cations are included in the PMM to differentiate between conventional and reformulated gasoline blends (Table 11.2): Reid vapor pressure (RVP), benzene content, aromatic content, sulfur content, ole"ns content, and the percent evaporated at 200 and 300 degrees Fahrenheit (E200 and E300). As of 2007, the sulfur content speci"cation for gasoline has been reduced to 30 parts per million (ppm) [1].
Conventional gasoline must comply with anti-dumping requirements aimed at preventing the quality of conventional gasoline from eroding as the reformulated gasoline program is implemented. Conventional gasoline must meet the Complex Model II compliance standards which cannot exceed average 1990 levels of toxic and nitrogen oxide emissions [2].
Cellulosic biomass feedstock supplies and costs are taken from the NEMS Renewable Fuels Model. Initial capital costs for biomass cellulosic ethanol were obtained from a research project reviewing cost estimates from multiple sources [3].
Operating costs and credits for excess electricity generated at biomass ethanol plants were obtained from a survey of literature
[4] and the USDA Agricultural Baseline Projections to 2019 [5].
Corn supply prices are estimated from the USDA baseline projections to 2019 [6]. The capital cost of a 50-million-gallon-per-year corn ethanol plant was assumed to be $84 million (2008 $). Operating costs of corn ethanol plants are obtained from USDA survey of ethanol plant costs [7]. Energy requirements are obtained from a study of carbon dioxide emissions associated with ethanol production [8].
Reformulated gasoline has been required in many areas in the United States since January 1995. In 1998, the EPA began certifying reformulated gasoline using the Complex Model, which allows re"ners to specify reformulated gasoline based on emissions reductions from their companies respective 1990 baselines or the EPAs 1990 baseline. The PMM re"ects Phase 2 reformulated gasoline requirements which began in 2000. The PMM uses a set of speci"cations that meet the Complex Model requirements, but it does not attempt to determine the optimal speci"cations that meet the Complex Model. (Table 11.3).
136 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module
+- " -4 " 656"" & ?&?""V 5??W &
Aromatics Benzene 2007 Reid Vapor Volume Volume Sulfur Ole"n Volume Percent Percent Pressure Percent Percent PPM Percent Evaporated Evaporated PADD (Max PSI) (Max) (Max) (Max) (Max) at 200o at 300o Conventional PADD I 9.6 26.0 1.1 30.0 11.6 47.1 82.0 PADD II 10.2 26.1 1.1 30.0 11.6 47.1 81.9 PADD III 9.9 26.1 1.1 30.0 11.6 47.1 81.9 PADD IV 10.8 26.1 1.1 30.0 11.6 47.1 81.9 PADD V 9.2 26.7 1.1 30.0 11.7 45.7 81.4 Reformulated PADD I 8.5 20.7 0.6 30.0 11.9 50.2 84.6 PADD II 9.5 18.5 0.8 30.0 7.1 50.8 85.2 PADD III 8.6 19.8 0.6 30.0 11.2 51.6 83.9 PADD IV 8.6 19.8 0.6 30.0 11.2 51.6 83.9 PADD V Nonattainment 7.9 22.0 0.70 20.0 6.0 49.0 90.0 CARB (attainment) 7.9 22.0 0.70 20.0 6.0 49.0 90.0 Max = Maximum.
PADD = Petroleum Administration for Defense District.
PPM = parts per million by weight.
PSI = pounds per square inch.
Benzene volume percent changed to 0.6 for all regions and type in 2011 to meet the MSAT2 ruling.
Source: U.S. Energy Information Administration, Office of Energy Analysis. Derived using U.S. EPAs Complex Model, and updated with U.S. EPAs gasoline projection survey Fuel Trends Report: Gasoline 1995-2005, January 2008, EPA420-R-08-002. (www.epa.gov/otaq/regs/fuels/rfg/properf/rfgperf.htm).
Table 11.3. Market share for gasoline types by Census Division East West East West Gasoline New Middle North North South South South Type/Year England Atlantic Central Central Atlantic Central Central Mountain Paci"c Conventional Gasoline 19 39 82 90 81 95 72 87 25 Reformulated Gasoline 12 61 18 10 19 5 28 13 75 Source: U.S. Energy Information Administration, Office of Energy Analysis. Derived from EIA-782C, Monthly Report of Prime Supplier Sales of Petroleum Products Sold for Local Consumption, January-December 2010.
As of January 2007, Oxygenated Gasoline is included within Conventional Gasoline.
AEO2012 assumes MTBE was phased out by the end of 2007 as a result of decisions made by the petroleum industry. Ethanol is assumed to be used in areas where reformulated gasoline is required. Federal reformulated gasoline (RFG) is blended with up to 15 percent ethanol in light-duty vehicles of model year 2001 and newer. Ethanol is also allowed to blend into conventional gasoline at up to 15 percent by volume, depending on its blending value and relative cost competitiveness with other gasoline blending components. However, current state regulation along with marketplace constraints limit the full penetration of E15 in the early part of the projection. EISA2007 de"nes a requirements schedule for having renewable fuels blended into transportation fuels by 2022.
Reid Vapor Pressure (RVP) limitations are effective during summer months, which are de"ned differently by consuming regions.
In addition, different RVP speci"cations apply within each re"ning region, or PADD. The PMM assumes that these variations in RVP are captured in the annual average speci"cations, which are based on summertime RVP limits, wintertime estimates, and seasonal weights.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 137
Petroleum Market Module Within the PMM, total gasoline demand is disaggregated into demand for conventional and reformulated gasoline by applying assumptions about the annual market shares for each type. In AEO2012 the annual market shares for each region re"ect actual 2010 market shares and are held constant throughout the projection. (See Table 11.3 for AEO2012 market share assumptions.)
? & " 6@"$
In order to account for ultra-low-sulfur diesel (ULSD) regulations related to Clean Air Act Amendments of 1990 (CAAA90), ultra-low-sulfur diesel is differentiated from other distillates. In NEMS, the Paci"c Region (Census Division 9) is required to meet CARB standards. Both Federal and CARB standards currently limit sulfur to 15 ppm.
AEO2012 incorporates the ULSD regulation "nalized in December 2000. ULSD is highway diesel that contains no more than 15 ppm sulfur at the pump. The ULSD regulation includes a phase-in period under the 80/20 rule, that requires the production of a minimum 80 percent ULSD for highway use between June 2006 and June 2010, and a 100-percent requirement for ULSD starting in 2011.
NEMS models ULSD as containing 7.5 ppm sulfur at the re"nery gate in 2006, phasing down to 7 ppm sulfur by 2011. This lower sulfur limit at the re"nery re"ects the general consensus that re"ners will need to produce diesel with a sulfur content below 10 ppm to allow for contamination during the distribution process.
Re"ners revamped (retro"tted) existing re"nery units to produce ULSD, representing two-thirds of highway diesel production, and that the remaining re"neries built new units. The capital cost of revamping is assumed to be 50 percent of the cost of adding a new unit.
The amount of ULSD downgraded to a lower value product because of sulfur contamination in the distribution system is assumed to be 7.8 percent at the start of the program, declining to 2.2 percent at full implementation. The decline re"ects the expectation that the distribution system will become more efficient at handling ULSD with experience.
A revenue loss is assumed to occur when a portion of ULSD that is put into the distribution system is contaminated and must be sold as a lower-value product. The amount of the revenue loss is estimated offline based on earlier NEMS results and is included in the AEO2012 ULSD price projections as a distribution cost. The revenue loss associated with the 7.8 percent downgrade assumption for 2009 is 0.7 cents per gallon. The revenue loss estimate declines to 0.2 cents per gallon after 2010 to re"ect the assumed decline to 2.2 percent.
The capital and operating costs associated with ULSD distribution are based on assumptions used by the EPA in the Regulatory Impact Analysis (RIA) of the rule [9]. Capital costs of 0.7 cent per gallon are assumed for additional storage tanks needed to handle ULSD during the transition period. These capital expenditures have been fully amortized by 2011. Additional operating costs for distribution of highway diesel of 0.2 cent per gallon are assumed over the entire projection period. Another 0.2-cent cost per gallon is assumed for lubricity additives. Lubricity additives are needed to compensate for the reduction of aromatics and high-molecular-weight hydrocarbons stripped away by the severe hydrotreating used in the desulphurization process.
Demand for highway-grade diesel, both 500 ppm and ULSD combined, is assumed to be equivalent to the total transportation distillate demand. Historically, highway-grade diesel supplies have nearly matched total transportation distillate sales, although some highway-grade diesel has gone to nontransportation uses such as construction and agriculture.
The energy content of ULSD is assumed to decline from that of 500 ppm diesel by 0.5 percent because undercutting and severe desulphurization will result in a lighter stream composition than that for 500 ppm diesel.
AEO2012 incorporates the nonroad, locomotive, and marine (NRLM) diesel regulation "nalized in May 2004. The PMM model has been revised to re"ect the nonroad rule and re-calibrated for market shares of highway, NRLM diesel, and other distillate (mostly heating oil, but excluding jet fuel and kerosene). The NRLM diesel rule follows the highway diesel rule closely and represents an incremental tightening of the entire diesel pool. The demand for high sulfur distillate is expected to diminish over time, while the demand for ULSD (both highway and NRLM) is expected to increase over time.
The "nal NRLM rule was implemented in multiple steps and required sulfur content for all NRLM diesel fuel produced by re"ners to be reduced to 500 ppm starting mid-2007. It also established a new ULSD limit of 15 ppm for nonroad diesel by mid-2010. For locomotive and marine diesel, the rule established an ULSD limit of 15 ppm in mid-2012.
138 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module End-Use product prices End-use petroleum product prices are based on marginal costs of production plus production-related "xed costs plus distribution costs and taxes. The marginal costs of production are determined within the LP and represent variable costs of production, including additional costs for meeting reformulated fuels provisions of the CAAA90. Environmental costs associated with controlling pollution at re"neries are implicitly assumed in the annual update of the re"nery investment costs for the processing units.
The costs of distributing and marketing petroleum products are represented by adding product-speci"c distribution costs to the marginal re"nery production costs (product wholesale prices). The distribution costs are derived from a set of base distribution markups (Table 11.4).
State and Federal taxes are also added to transportation fuels to determine "nal end-use prices (Tables 11.5 and 11.6). Recent tax trend analysis indicates that State taxes increase at the rate of in"ation, therefore, State taxes are held constant in real terms throughout the projection. This assumption is extended to local taxes which are assumed to average 2 cents per gallon [10].
Federal taxes are assumed to remain at current levels in accordance with the overall AEO2012 assumption of current laws and regulations. Federal taxes are not held constant but de"ated as follows:
Federal Tax product, year = Current Federal Tax product /GDP De"ator year Crude oil quality In the PMM, the quality of crude oil is characterized by average gravity and sulfur levels. Both domestic and imported crude oil are divided into "ve categories as de"ned by the ranges of gravity and sulfur shown in Table 11.7.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 139
Petroleum Market Module Table 11.4. Petroleum product end-use markups by sector and Census Division 2010 dollars per gallon Census Division East West East West New Middle North North South South South Sector/Product England Atlantic Central Central Atlantic Central Central Mountain Paci"c Residential Sector Distillate Fuel Oil 0.45 0.50 0.25 0.21 0.38 0.24 0.37 0.29 0.36 Kerosene 1.37 0.75 0.30 0.32 0.22 0.34 0.34 0.77 0.87 Lique"ed Petroleum Gases 1.32 1.36 0.83 0.58 1.31 1.15 1.02 0.97 1.15 Commercial Sector Distillate Fuel Oil 0.37 0.30 0.18 0.09 0.21 0.13 0.13 0.12 -0.17 Gasoline 0.15 0.15 0.14 0.13 0.13 0.15 0.14 0.18 0.19 Kerosene 1.38 0.57 0.28 0.34 0.22 0.30 0.30 1.01 1.08 Lique"ed Petroleum Gases 0.56 0.82 0.63 0.63 0.81 0.72 0.76 0.79 0.65 Low-Sulfur Residual Fuel Oil 1.15 -0.04 0.78 0.73 0.12 0.15 0.06 0.00 0.14 Utility Sector Distillate Fuel Oil 0.31 0.25 0.10 -0.04 -0.01 -0.54 -0.39 0.21 -0.24 1
Residual Fuel Oil 0.64 0.76 0.41 0.33 0.64 0.39 0.24 0.32 0.47 Transportation Sector Distillate Fuel Oil 0.35 0.24 0.17 0.14 0.18 0.14 0.14 0.16 0.24 2
E85 0.14 0.14 0.11 0.10 0.11 0.12 0.09 0.15 0.15 Gasoline 0.18 0.18 0.15 0.14 0.14 0.15 0.12 0.20 0.19 1
High-Sulfur Residual Fuel Oil 1.02 0.45 -0.19 0.15 -0.57 0.10 -0.50 -0.55 0.00 Jet Fuel 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.00 0.02 Lique"ed Petroleum Gases 0.48 0.72 0.96 0.97 0.83 0.98 1.01 0.92 0.94 Industrial Sector Asphalt and Road Oil 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Distillate Fuel Oil 0.38 0.39 0.32 0.25 0.26 0.22 0.16 0.16 -0.21 Gasoline 0.18 0.17 0.14 0.13 0.14 0.16 0.14 0.19 0.19 Kerosene -0.82 -0.04 0.04 0.00 -0.02 0.18 0.01 0.40 0.54 Lique"ed Petroleum Gases 0.97 0.90 0.61 0.61 0.74 0.53 0.24 0.56 0.83 Low-Sulfur Residual Fuel Oil 0.91 -0.10 0.79 0.73 0.10 0.24 0.08 0.04 0.19 1
Negative values indicate that average end-use sales prices were less than wholesale prices. This often occurs with residual fuel which is produced as a byproduct when crude oil is re"ned to make higher-value products like gasoline and heating oil.
2 E85 refers to a blend of 85 percent ethanol (renewable) and 15 percent motor gasoline (non-renewable). To address cold starting issues, the percentage of ethanol varies seasonally. The annual average ethanol content of 74 percent is used.
Sources: Markups based on data from Energy Information Administration (EIA), Form EIA-782A, Re"ners/Gas Plant Operators Monthly Petroleum Product Sales Report; EIA, Form EIA-782B, Resellers/Retailers Monthly Petroleum Report Product Sales Report; EIA, Form FERC-423, Monthly Report of Cost and Quality of Fuels for Electric Plants; EIA, Form EIA-759 Monthly Power Plant Report; EIA, State Energy Data Report 2010, Consumption (June 2011); EIA, State Energy Data 2010: Prices and Expenditures (June 2011).
140 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module
+- X"" "= " 6" "" & -4!? &<4
2010 dollars per gallon Census Division East West East West New Middle North North South South South Year/Product England Atlantic Central Central Atlantic Central Central Mountain Paci"c 1
Gasoline 0.31 0.27 0.25 0.25 0.21 0.22 0.22 0.24 0.24 Diesel 0.27 0.32 0.22 0.22 0.22 0.19 0.19 0.22 0.31 Lique"ed Petroleum Gases 0.13 0.13 0.18 0.20 0.19 0.18 0.14 0.15 0.06 2
E85 0.22 0.19 0.18 0.17 0.14 0.15 0.15 0.16 0.17 Jet Fuel 0.07 0.05 0.00 0.04 0.08 0.08 0.03 0.04 0.03 1
Tax also applies to gasoline consumed in the commercial and industrial sectors.
2 E85 refers to a blend of 85 percent ethanol (renewable) and 15 percent motor gasoline (non-renewable). To address cold starting issues, the percentage of ethanol varies seasonally. The annual average ethanol content of 74 percent is used.
Source: Compilation of United States Fuel Taxes, Inspection, Fees and Environmental Taxes and Fees, Defense Energy Support Center, Editions 2011-09, May 18, 2011).
+- P "= & " -
nominal dollars per gallon Product Tax Gasoline 0.18 Diesel 0.24 Jet Fuel 0.04 3
Lique"ed Petroleum Gases 0.043 M851 0.09 2
E85 0.20 1
85 percent methanol and 15 percent gasoline.
2 74 percent ethanol and 26 percent gasoline.
3 2010 data-based on EPACT05: excise tax is 4.3 cents/gal after 9-30-2011 and 18.3 cents/gal prior to that. A credit of 50 cents/gal was also applied between 10-1-06 and 9-30-09.
Sources: Omnibus Budget Reconciliation Act of 1993 (H.R. 2264); Tax Payer Relief Act of 1997 (PL 105-34), Clean Fuels Report (Washington, DC, April 1998) and Energy Policy Act of 2005 (PL 109-58). IRS Internal Revenue Bulletin 2006-43 available on the web at www.irs.gov/pub/irs-irbs/irb06-43.pdf
+- [ ! "
Sulfur Gravity Crude Oil Categories (percent) (degrees API)
Low Sulfur Light 0 - 0.5 25 - 60 Medium Sulfur Heavy 0.35-1.1 26 - 40 High Sulfur Light > 1.1 >32 High Sulfur Heavy > 1.1 24 - 33 High Sulfur Very Heavy > 0.9 <23 Source: U.S. Energy Information Administration, Office of Energy Analysis. Derived from EI-810, Monthly Re"nery Report data.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 141
Petroleum Market Module A composite crude oil with the appropriate yields and qualities is developed for each category by averaging the characteristics of speci"c crude oil streams in the category. While the domestic and foreign categories are the same, the composite crudes for each category may differ because different crude streams make up the composites. For domestic crude oil, estimates of total regional production are made "rst, then shared out to each of the "ve categories based on historical data. For imported crude oil, a separate supply curve is provided for each of the "ve categories. Each import supply curve is linked to a world oil supply market balance for that crude type, such that the quantity of crude oil imported depends on the economic competition with use by the rest of the world.
Capacity expansion The PMM allows for capacity expansion of all processing unit types including atmospheric distillation, vacuum distillation, hydrotreating, coking, "uid catalytic cracking, hydrocracking, and alkylation. Capacity expansion occurs by processing unit, starting from regional capacities established using historical data.
Expansion occurs in NEMS when the value received from the additional product sales exceeds the investment and operating costs of the new unit. The investment costs assume a "nancing ratio of 60 percent equity and 40 percent debt, with a hurdle rate and an after-tax return on investment of about 9 percent. Capacity expansion plans are determined every 3 years. For example, the PMM looks ahead in 2011 and determines the optimal capacities given the estimated demands and prices expected in the 2014 projection year. The PMM then allows any of that capacity to be built in each of the projection years 2012, 2013, and 2014. At the end of 2014 the cycle begins anew, looking ahead to 2017. Atmospheric Crude Unit (ACU) capacity under construction that is expected to begin operating in the future is added to existing capacities in their respective start year. Capacity expansion is also modeled for corn and cellulosic ethanol, coal-to-liquids, gas-to-liquids, and biomass-to-liquids production.
Alternative fuel technology characteristics The PMM explicitly models a number of liquid fuels technologies that do not require petroleum feedstock. These technologies produce both fuel-grade products for blending with traditional petroleum products, and alternative feedstock for the traditional petroleum re"nery (Table 11.8).
Estimates of capital costs, operating cost, and process yield for these technologies are shown in Table 11.9. Costs are de"ned for 2010 and are escalated in the PMM using the GDP de"ator. Owners Capital Cost is de"ned as the anticipated cost for a fully continuous, commercial scale plant. However, some of the technologies have not yet been proven at a commercial scale. As a result, a technology optimism factor is applied to the owners capital cost for the "rst plant of those technologies. For the next four plants, the capital cost decreases linearly such that the "fth plant is built at the owners capital cost de"ned in the table. Following this phase, capital cost is decreased at a rate corresponding to the maturity of the components that make up the technology, re"ecting the principle of learning by doing. This principle is implemented in the PMM in the same way as it is in the Electricity Market Module. Model parameters are shown in Table 11.10.
Table 11.8 Alternative fuel technology product type Technology Product Type Biochemical Corn Ethanol Fuel Grade Barley Ethanol Fuel Grade Cellulosic Ethanol Fuel Grade Thermocatalytic Biomass Fisher-Tropsch Fuel Grade/Re"nery Feed Pyrolysis Oil Re"nery Feed Methyl Ester Biodiesel Fuel Grade Renewable Diesel Fuel Grade Biomass-to-Liquids (CBTL) Fuel Grade/Re"nery Feed Natural-Gas-to-Liquids (GTL) Fuel Grade/Re"nery Feed Coal-to-Liquids (CTL) Fuel Grade/Re"nery Feed Source: U.S. Energy Information Administration, Office of Energy Analysis.
142 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module Table 11.9. Alternative fuel technology characteristics United States Gulf Coast Base Total Total AEO2011 2020 Basis Online Nameplate Overnight Contingency Overnight Variable Fixed Thermal (2011$) Year Capacity1 Capital Factors2,3 Capital4 Cost5 O&M6 Efficiency7 Energy barrels/day $/daily barrel Project Optimism $/daily barrel $/barrel $/barrel Percent Biochemical Corn Ethanol - 6,523 $24,147 5% 0% $27,591 $68.83 - 54%
Advanced Ethanol 2011 4,240 $26,562 5% 0% $30,350 $78.41 - 49%
Cellulosic Ethanol (1st plant) 2012 3,700 $99,948 5% 25% $142,755 $49.39 $12.41 28%
Cellulosic Ethanol (50th plant) - 3,700 $99,948 5% 25% $82,428 $49.39 $12.41 28%
Thermocatalytic Coal/Biomass FT Liquids 2015 30,000 $136,731 10% 2.5% $151,014 $12.46 $21.74 45%
Biomass FT Liquids (1st plant) 2012 3,143 $242,560 10% 25% $326,703 $15.65 $39.11 47%
Biomass FT Liquids (50th plant) - 3,143 $242,560 10% 25% $246,608 $15.65 $39.11 47%
Pyrolysis Oil (1st plant) 2014 687 $56,450 10% 25% $78,726 $31.12 $24.56 52%
Pyrolysis Oil (50th plant) 2014 687 $56,450 10% 25% $54,770 $31.12 $24.56 52%
Coal FT Liquids 2015 50,000 $136,856 10% 0% $147,465 $12.68 $20.18 43%
Natural Gas FT Liquids8 2017 34,000 $68,448 10% 0% $73,923 $48.36 $10.37 59%
Methyl Ester Biodiesel - 1,305 $26,747 5% 0% $28,085 $132.24 - 36%
Nonester Renewable Diesel 2010 2,000 $10,761 5% 2.5% $11,471 $129.81 $1.80 38%
1 For all processes except corn ethanol and FAME biodiesel, annual capacity refers to the capacity of one plant as de"ned in the Petrolem Market Module of NEMS. For corn ethanol and FAME biodiesel, annual capacity is the most common plant size as of 2008.
2 Contingency is de"ned by the Amercian Association of Cost Engineers as a speci"c provision for unforeseeable elements in costs within a de"ned project scope; particularly important where previous experience has shown that unforeseeable events which will increase costs are likely to occur.
3 The technology optimism factor is applied to the "rst four units of an unproven design, re"ecting a demonstrated tendency to underestimate costs for a "rst-of-a-kind unit.
4 Total Overnight cost including contingency factors, excluding regional multipliers, learning effects, and interest charges.
5 Variable Operating and Maintenance costs (O&M) include sales of electricity to the grid and coproduct value where applicable.
6 For Corn Ethanol, Advanced Ethanol, and Biodiesel, "xed costs are included in Variable Operating Cost.
7 A soybean oil mass yield of 20% is assumed in the crush facility in order to compute yield. Efficiency is de"ned as the heat content of the liquid products divided by the heat content of the feedstock.
8 While these costs are for a Gulf Coast facility, the costs in other regions, particularly Alaska, are expected to be much higher.
Sources: The values shown in this table are developed by the Energy Information Administration, Office of Electricity, Coal, Nuclear, and Renewables Analysis, from analysis of reports and discussions with various sources from industry, government, and the Department of Energy Fuel Offices and National Laboratories. They are meant to represent the cost and performance of typical plants under normal oprating conditions for each technology. Key sources reviewed are listed in Notes and Sources at the end of the chapter.
Variable operating cost includes the cost of feedstock, utility requirements, coproduct credit, and other costs that depend on capacity utilization, and they represent the expected costs to operate a fully continuous, commercial-scale plant for each technology. The breakdown is shown in Table 11.11.
Alternative fuels market dynamics In the PMM, overnight capital costs are amortized and then added to variable and "xed costs in order to provide a cost of production [11]. As a result of this inclusion of capital cost in the cost of production, a given technologys production cost has the potential to become more or less attractive relative to other technologies as plants are built.
While cost of production de"nes a basis for comparison, market competition is often de"ned by the required feedstock. For example, technologies requiring greases and oils (biodiesel and renewable diesel) compete with each other for that feedstock, limiting the overall market share of each technology. As a consequence of this and the Renewable Fuels Standard, cellulosic ethanol and Biomass to Liquids (BTL) technologies, which include Fischer-Tropsch and Pyrolysis, compete directly with each other. By contrast, technologies like Gas-to-Liquids and Coal-to-Liquids compete more directly with petroleum fuels, since their feedstock are more similar to petroleum and their fuels are not required by the RFS.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 143
Petroleum Market Module Table 11.10. Alternative fuel technology learning parameters Plants Built 1st of a Kind 5th of a Kind 32nd of a Kind Mature 0% 33% 67% 0% 100%
Cellulosic Ethanol Decline Factor 0.079 0.415 0.014 0.152 0.072 Cumulative Capacity 1.25 0.708 0.754 0.288 0.75 Plant % 0% 0% 100% 0% 100%
Biomass Fischer-Tropsch Decline Factor 0.079 0.415% 0.014 0.152 0.072 Cumulative Capacity 1.250 1.128 1.126 0.000 1.126 Plant % 0% 18% 82% 0% 100%
Pyrolysis Oil Decline Factor 0.079 0.418 0.014 0.152 0.072 Cumulative Capacity 1.28 0.386 0.923 0.155 0.923 Source: U.S. Energy Information Administration.
Table 11.11. Alternative fuel technology variable costs1 AEO2011 2020 Basis (Real 2011 $/barrel)Technology Total Feedstock Cost Net Utility Cost2 Coproduct Credit Other Variable3 Biochemical - - - - -
Corn Ethanol $68.83 $70.69 $10.91 $19.78 $7.01 Barley Ethanol $78.41 $89.73 -$3.99 $14.34 $7.01 Cellulosic Ethanol $49.39 $23.64 -$16.83 - $42.58 Thermocatalytic - - - - -
Coal/Biomass FT Liquids $12.46 $18.16 $9.57 - $3.76 Biomass FT Liquids $15.65 $22.42 -$11.16 - $4.39 Pyrolysis Oil $31.12 $20.54 $0.00 $3.64 $14.21 Coal FT Liquids $12.68 $18.39 -$9.57 - $3.86 Natural Gas FT Liquids $48.36 $47.11 $0.00 - $1.25 Methyl Ester Biodiesel $132.24 $124.87 $1.61 $0.74 $6.50 Nonester Renewable Diesel $129.81 $127.27 $0.11 - $2.43 1
This table is based on the AEO2011 Reference case projections for year 2020.
2 Sales of electricity to the Grid from cogeneration are included in net utility costs.
3 These costs are speci"c to each technology. Often cooling water, catalyst, and chemicals are applied here. For cellulosic ethanol, this includes enzyme costs and therefore is expected to decrease from $50.53/barrel in 2010 to $30.48/barrel in 2035.
Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear, and Renewables Analysis.
144 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module Biofuels supply The PMM provides supply functions on an annual basis through 2035 for ethanol produced from both corn and cellulosic biomass to produce transportation fuel. It also assumes that small amounts of vegetable oil and animal fats are processed into biodiesel, a blend of methyl esters suitable for fueling diesel engines.
Corn feedstock supplies and costs are provided exogenously to NEMS. Feedstock costs re"ect credits for co-products (livestock feed, corn oil, etc.). Feedstock supplies and costs re"ect the competition between corn and its co-products and alternative crops, such as soybeans and their co-products.
Cellulosic (biomass) feedstock supply and costs are provided by the Renewable Fuels Module in NEMS.
The Federal motor fuels excise tax credit of 45 cents per gallon of ethanol (4.5 cents per gallon credit to gasohol at a 10-percent volumetric blending portion) is no longer applied within the model projections as the credit expired after 2011.
To model the Renewable Fuels Standard in EISA2007, several assumptions were required. In addition to using the text of the legislation, it was also assumed that rules promulgated under the RFS in EPACT05 would govern the administration of the EISA2007 RFS through June 2010. After that point, the administration is governed by the most recent RFS rulemaking.
The penetration of cellulosic ethanol into the market is limited before 2012 to the likely projects currently expected to produce approximately 4 million gallons per year.
Methyl ester biodiesel production contributes 1.5 credits towards the advanced mandate.
Renewable diesel fuel, including that from Pyrolysis oil, and Fischer-Tropsch diesel contribute 1.7 credits toward the cellulosic mandate.
Renewable gasoline, including that from Pyrolysis oil, and Fischer-Tropsch naphtha contribute 1.54 credits toward the cellulosic mandate.
Imported Brazilian sugarcane ethanol counts towards the advanced renewable mandate. Supply curves for sugarcane ethanol imports allow for substantial penetration by 2022 (1.5 billion gallons) into the U.S. advanced fuel supply pool, after which sugarcane ethanol remains competitive due to its relatively low production cost, availability, and the expiration of the 54 cents/
gallon import tariff on Jan. 1, 2012. Ample sugarcane ethanol supply for export from Brazil is supported by outside forecasts
[12]. In addition, cellulosic ethanol would be available for export to the U.S. (largely from bagasse feedstock) but this supply is limited in part due to competition with the growing use of sugarcane residue for electricity generation in Brazil.
Separate biofuel waivers can be activated by the EPA for each of the four RFS fuel categories. In years beyond 2022, the RFS mandate levels continue to increase toward 36 billion gallons. When this value is reached, the volumes continue to rise with U.S.
demand for transportation fuel.
It is assumed that biodiesel and BTL diesel may be consumed in diesel engines without signi"cant infrastructure modi"cation (either vehicles or delivery infrastructure).
Ethanol is assumed to be consumed as E10, E15 or E85, with no intermediate blends. The cost of placing E85 pumps at the most economic stations is spread over diesel and gasoline.
To accommodate the ethanol requirements in particular, transportation modes are expanded or upgraded for E10, E15 and E85, and it is assumed that most ethanol originates from the Midwest, with nominal transportation costs ranging from a low of 1.7 cents per gallon for expanded distribution in the Midwest, to as high as 2.6 cents per gallon for the Southeast and West Coast.
For E85 dispensing stations, it is assumed the average cost of a retro"t and new station is about $45,000 per station, which translates into an incremental cost per gallon ranging from 26 cents in 2013 to 3 cents by 2020, depending on the average sales per dispenser.
The total projected incremental nominal infrastructure cost (transportation, distribution, dispensing) for E85 varies from 27 cents per gallon of E85 in 2013 to 5 cents per gallon in 2020.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 145
Petroleum Market Module Interregional transportation is assumed to be by rail, ship, barge, and truck, and the associated costs are included in PMM. A subsidy is offered by the Department of Agricultures Commodity Credit Corporation for the production of biodiesel. In addition, the American Jobs Creation Act of 2004 provided an additional tax credit of $1 per gallon of soybean oil for biodiesel and 50 cents per gallon for yellow grease biodiesel through 2006, and EPACT05 extended the credit to 2008. The Emergency Stabilization Act of 2008 extended it again to 2009 and increased the yellow grease credit to $1 per gallon Non-biofuel alternative supply Gas-to-liquids (GTL) facilities convert natural gas into distillates, and are assumed to be built if the prices for lower-sulfur distillates reach a high enough level to make it economic. In the PMM, gas-to-liquids facilities are assumed to be built only on the North Slope of Alaska, where the distillate product is transported on the Trans-Alaskan Pipeline System (TAPS) to Valdez and shipped to markets in the lower 48 States. The earliest start date for a GTL facility is set at 2017. Since the Alaska Natural Gas Transportation System (ANGTS) is not economic in the AEO2012, the Alaska GTL plant has access to associated gas resources currently used to increase oil recovery. The transportation cost to ship the GTL product from the North Slope to Valdez along the TAPS is assumed to be the price set to move oil (i.e. the TAPS revenue recovery rate). This rate is a function of allowable costs, pro"t, and "ow, and can change over the projection.
It is also assumed that coal-to-liquids (CTL) facilities will be built when low-sulfur distillate prices are high enough to make them economic. Additionally, a process which allows co-"ring of coal with biomass (CBTL) is explicitly modeled for producers who wish to receive RFS credit for a portion of their product. A 50,000-barrel-per-day CTL facility is assumed to cost about $7 billion in initial capital investment (2009 dollars) while a 30,000-barrel-per-day CBTL facility is expected to cost about $4.4 billion. These facilities could be built near existing re"neries. For the East Coast, potential CTL facilities could be built near the Delaware River basin; for the Central region, near the Illinois River basin or near Billings, Montana; and for the West Coast, in the vicinity of Puget Sound in Washington State. It is further assumed that CTL facilities can only be built after 2014.
Gasi"cation of petroleum coke (petcoke) and heavy oil (asphalt, vacuum resid, etc.) is represented in AEO2012. The PMM assumes petcoke to be the primary feedstock for gasi"cation, which in turn could be converted to either combined heat and power (CHP) or hydrogen production based on re"nery economics. A typical gasi"cation facility is assumed to have a capacity of 2,000 tons-per-day (TPD), which includes the main gasi"er and other integrated units in the re"nery such as air separation unit (ASU), syngas clean-up, sulfur recovery unit (SRU), and two downstream process options - CHP or hydrogen production. Currently, there is more than 5,000 TPD of gasi"cation capacity in the United States that produces CHP and hydrogen.
! 6-$" /V!\ W Electricity consumption in the re"nery is a function of the throughput of each unit. Sources of electricity consist of re"nery power generation, utility purchases, re"nery CHP, and merchant CHP. Power generators and CHP plants are modeled in the PMM linear program as separate units which are allowed to compete along with purchased electricity. Both the re"nery and merchant CHP units provide estimates of capacity, fuel consumption, and electricity sales to the grid based on historical parameters.
Re"nery sales to the grid are estimated using the following percentages which are based on 2005 data:
Region Percent Sold To Grid PADD I 67.0 PADD II 0.9 PADD III 2.2 PADD IV 0.9 PADD V 45.4 Source: U.S. Energy Information Administration. Derived using EIA-860B, Annual Electric Generators Report-Nonutility.
Merchant CHP plants are de"ned as non-re"ner owned facilities located near re"neries to provide energy to the open market and to the neighboring re"nery. These sales occur at a price equal to the average wholesale price of electricity in each PMM region, which are obtained from the Electricity Market Model.
Short-term methodology Petroleum balance and price information for 2011 are projected at the U.S. level in the Short-Term Energy Outlook, (STEO). The PMM adopts the STEO results for 2011, using regional estimates derived from the national STEO projections.
146 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Petroleum Market Module Legislation and regulation The Tax Payer Relief Act of 1997 reduced excise taxes on lique"ed petroleum gases and methanol produced from natural gas. The reductions set taxes on these products equal to the Federal gasoline tax on a Btu basis.
Title II of CAAA90 established regulations for oxygenated and reformulated gasoline and reduced-sulfur (500 ppm) on-highway diesel fuel. These are explicitly modeled in the PMM. Reformulated gasoline represented in the PMM meets the requirements of phase 2 of the Complex Model, except in the Paci"c region where it meets CARB 3 speci"cations.
AEO2012 re"ects Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements "nalized by EPA in February 2000. This regulation requires that the average annual sulfur content of all gasoline used in the United States be phased-down to 30 ppm between the years 2004 and 2007. The 30 ppm annual average standard was not fully realized in conventional gasoline until 2008 due to allowances for small re"neries.
AEO2012 re"ects Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements "nalized by the EPA in December 2000. Between June 2006 and June 2010, this regulation requires that 80 percent of highway diesel supplies contain no more than 15 ppm sulfur while the remaining 20 percent of highway diesel supplies contain no more than 500 ppm sulfur. After June 2010, all highway diesel is required to contain no more than 15 ppm sulfur at the pump.
AEO2012 re"ects nonroad locomotive and marine (NRLM) diesel requirements "nalized by the EPA in May 2004. Between June 2007 and June 2010, this regulation requires that nonroad diesel supplies contain no more than 15 ppm sulfur. For locomotive and marine diesel, the action establishes a NRLM limit of 15 ppm in mid-2012.
AEO2012 represents major provisions in the Energy Policy Act of 2005 (EPACT05) concerning the petroleum industry, including:
- 1) removal of oxygenate requirement in RFG; and 2) extension of tax credit of $1 per gallon for soybean oil biodiesel and $0.50 per gallon for yellow grease biodiesel through 2008.
The Emergency Stabilization Act of 2008 extended the soybean oil for biodiesel tax credit again to 2009 and increased the yellow grease credit to $1 per gallon.
AEO2012 includes provisions outlined in the Energy Independence and Security Act of 2007 (EISA2007) concerning the petroleum industry, including a Renewable Fuels Standard (RFS) increasing total U.S. consumption of renewable fuels. Although the statute calls for higher levels, due to uncertainty about whether the new RFS schedule can be achieved and the stated mechanisms for reducing the cellulosic biofuel schedule, the "nal schedules in PMM were assumed to be: 1) 30.9 billion gallons in 2023 for all fuels; 2) 15.9 billion gallons in 2023 for advanced biofuels; 3) 10.9 billion gallons in 2023 for cellulosic biofuel; 4) 1 billion gallons of biodiesel by 2023 [13].
AEO2012 includes the EPA Mobil Source Air Toxics (MSAT 2) rule which includes the requirement that all gasoline products (including reformulated and conventional gasoline) produced at a re"nery during a calendar year will need to contain no more than 0.61 percent benzene by volume. This does not include gasoline produced or sold in California, which is already covered by the current California Phase 3 Reformulated Gasoline Program.
AEO2012 does not include Californias Low Carbon Fuel Standard which aims to reduce the Carbon Intensity (CI) of gasoline and diesel fuels in that State by 10% respectively from 2012 through 2020. As of December 2011, the U.S. District Court for the Eastern Division of California ruled in favor of numerous trade groups that claimed the LDFS violated the Interstate Commerce Clause of the U.S. Constitution, thus locking its enforcement by the California Air Resources Board.
AEO2012 includes mandates passed in 2010 by Connecticut, Maine, New York, and New Jersey that aim to lower the sulfur content of all heating oil to ultra-low-sulfur diesel over different time schedules, as well as transition to a 2% biodiesel content by mid-2011 in the case of Maine and Connecticut.
Due to the uncertainty surrounding compliance options, AEO2012 did not include any explicit modeling treatment of the International Maritime Organizations MARPOL Annex 6 rule covering cleaner marine fuels and ocean ship engine emissions.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 147
Petroleum Market Module Notes and sources
[1] U.S. Environmental Protection Agency, Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements, February 2000 (Washington, DC).
[2] Federal Register, U.S. Environmental Protection Agency, 40 CFR Part 80, Regulation of Fuels and Fuel Additives:
Standards for Reformulated and Conventional Gasoline, Rules and Regulations, p. 7800, (Washington, DC, February 1994).
[3] Marano, John, Alternative Fuels Technology Pro"le: Cellulosic Ethanol, March 2008.
[4] Ibid.
[5] U.S. Department of Agriculture, USDA Agricultural Baseline Projections to 2019, February 2009, www.ers.usda.
gov/publications/oce091.
[6] Ibid
[7] Shapouri Hosein; Gallagher, Paul; and Graboski, Mike. USDAs 1998 Ethanol Cost-of-Production Survey. January 2002.
[8] Marland, G. and A.F. Turhollow. 1991. CO2 Emissions from the Production and Combustion of Fuel Ethanol from Corn. Energy, 16(11/12):1307-1316.
[9] U.S. Environmental Protection Agency, Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Requirements, EPA420-R-00-026 (Washington, DC, December 2000).
[10] American Petroleum Institute, How Much We Pay for Gasoline: 1996 Annual Review, May 1997.
[11] Economic lifetime is 15 years for cellulosic ethanol, biomass Fischer-Tropsch, and Pyrolysis Oil. It is 20 years for all others. Required rate of return is calculated using a 60:40 debt to equity ratio and the capital asset pricing model for the cost of equity.
[12] www.agrievolution.com/atti/brasile_02.ppt.
[13] The 2023 RFS levels used in the PMM reinstates the temporary reductions (1.1 billion gallons) that were needed in 2022 for the all fuels, advanced biofuels, and cellulosic biofuel categories.
148 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Coal Market Module THIS PAGE INTENTIONALLY LEFT BLANK Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2012, DOE/EIA-M060(2012) (Washington, DC, 2012).
Key assumptions Coal production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs.
The key assumptions underlying the coal production modeling are:
As capacity utilization increases, higher minemouth prices for a given supply curve are projected. The opportunity to add capacity is allowed within the modeling framework if capacity utilization rises to a pre-determined level, typically in the 80 percent range. Likewise, if capacity utilization falls, mining capacity may be retired. The amount of capacity that can be added or retired in a given year depends on the level of capacity utilization, the supply region, and the mining process (underground or surface). The volume of capacity expansion permitted in a projection year is based upon historical patterns of capacity additions.
Between 1980 and 2000, U.S. coal mining productivity increased at an average rate of 6.6 percent per year, from 1.93 to 6.99 short tons per miner per hour. The major factors underlying these gains were interfuel price competition, structural change in the industry, and technological improvements in coal mining. Since 2000, however, growth in overall U.S. coal mining productivity has been negative, declining at a rate of 2.3 percent per year to 5.55 short tons per miner hour in 2010.
By region, productivity in most of the coal producing basins represented in the NEMS Coal Market Module has declined some during the past decade. In the Central Appalachian coal basin, which has been mined extensively, productivity declined by 45 percent between 2000 and 2010, corresponding to an average decline of 5.9 percent per year. While productivity declines have been more moderate at the highly productive mines in Wyomings Powder River Basin, overall coal mining productivity still fell by 24 percent between 2000 and 2010, corresponding to an average rate of decline of 2.7 percent per year.
Over the projection period, labor productivity is expected to decline in a number of coal supply regions, re"ecting the trend of the previous ten years. Higher stripping ratios and the added labor needed to maintain more extensive underground mines offset productivity gains achieved from improved equipment, automation, and technology. Productivity in some areas of the East is projected to decline as operations move from mature coal"elds to marginal reserve areas. Regulatory restrictions on surface mines and fragmentation of underground reserves limit the bene"ts that can be achieved by Appalachian producers from economies of scale.
In the CMM, different rates of productivity improvement are assumed for each of the 41 coal supply curves used to represent U.S. coal supply. These estimates are based on recent historical data and expectations regarding the penetration and impact of new coal mining technologies [2]. Data on labor productivity are provided on a quarterly and annual basis by individual coal mines and preparation plants on the U.S. Mine Safety and Health Administrations Form 7000-2, Quarterly Mine Employment and Coal Production Report and the U.S. Energy Information Administrations Form EIA-7A, Coal Production and Preparation Report. In the Reference case, overall U.S. coal mining labor productivity declines at rate of 1.4 percent per year between 2010 and 2035. Reference case projections of coal mining productivity by region are provided in Table 12.1.
In the AEO2012 Reference case, the wage rate for U.S. coal miners increases by 1.0 percent per year and mine equipment costs are assumed to remain constant in 2010 dollars (i.e., increase at the general rate of in"ation) over the projection period.
Coal distribution The coal distribution submodule of the CMM determines the least-cost (minemouth price plus transportation cost) supplies of coal by supply region for a given set of coal demands in each demand sector using a linear programming algorithm. Production and distribution are computed for 14 supply (Figure 11) and 16 demand regions (Figure 12) for 49 demand subsectors.
The projected levels of coal-to-liquids, industrial steam, coking, and residential/commercial coal demand are provided by the petroleum market, industrial, commercial, and residential demand modules, respectively; electricity coal demands are projected by the EMM; coal imports and coal exports are projected by the CMM based on non-U.S. supply availability, endogenously determined U.S. import demand, and exogenously determined world coal import demands (non-U.S.).
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 151
Coal Market Module Table 12.1. Coal mining productivity by region short tons per miner hour Average Annual Supply Region 2010 2015 2020 2025 2030 2035 Growth 10-35 Northern Appalachia 3.42 3.02 2.89 2.72 2.57 2.47 -1.3%
Central Appalachia 2.27 1.57 1.28 1.08 0.94 0.84 -3.9%
Southern Appalachia 1.97 1.51 1.35 1.20 1.05 0.97 -2.8%
Eastern Interior 4.11 3.99 3.85 3.68 3.54 3.46 -0.7%
Western Interior 2.43 1.96 1.77 1.59 1.43 1.33 -2.4%
Gulf Lignite 6.84 5.41 4.81 4.28 3.81 3.54 -2.6%
Dakota Lignite 13.43 12.20 11.66 11.15 10.65 10.34 -1.0%
Western Montana 17.15 13.95 13.86 13.38 12.42 12.31 -1.3%
Wyoming, Northern Powder River Basin 32.10 27.14 24.91 22.87 20.99 19.86 -1.9%
Wyoming, Southern Powder River Basin 36.27 30.67 28.15 25.84 23.71 22.44 -1.9%
Western Wyoming 7.26 6.46 6.10 5.79 5.52 5.34 -1.2%
Rocky Mountain 5.34 4.44 4.07 3.73 3.42 3.22 -2.0%
Arizona/New Mexico 8.35 7.19 7.16 6.44 6.00 5.71 -1.5%
Alaska/Washington 6.96 5.97 5.54 5.14 4.76 4.53 -1.7%
U.S. Average 5.55 4.64 4.92 4.65 4.15 3.88 -1.4%
Source: U.S. Energy Information Administration, AEO2012 National Energy Modeling System run REF2012.D020112C.
The key assumptions underlying the coal distribution modeling are:
Base-year (2010) transportation costs are estimates of average transportation costs for each origin-destination pair without differentiation by transportation mode (rail, truck, barge, and conveyor). These costs are computed as the difference between the average delivered price for a demand region (by sector and for export) and the average minemouth price for a supply curve. Delivered price data are from Form EIA-3, Quarterly Coal Consumption Report-Manufacturing Plants, Form EIA-5, Quarterly Coke Consumption and Quality Report, Coke Plants, Form EIA-923, Power Plant Operations Report, and the U.S. Bureau of the Census Monthly Report EM-545. Minemouth price data are from Form EIA-7A, Coal Production and Preparation Report.
For the electricity sector only, a two-tier transportation rate structure is used for those regions which, in response to rising demands or changes in demands, may expand their market share beyond historical levels. The "rst-tier rate is representative of the historical average transportation rate. The second-tier transportation rate is used to capture the higher cost of expanded shipping distances in large demand regions. The second tier is also used to capture costs associated with the use of subbituminous coal at units that were not originally designed for its use. This cost is estimated at $0.10 per million Btu (2000 dollars) [3].
Coal transportation costs, both "rst- and second-tier rates, are modi"ed over time by two regional (east and west) transportation indices. The indices, calculated econometrically, are measures of the change in average transportation rates for coal shipments on a tonnage basis, that occurs between successive years for coal shipments. An east index is used for coal originating from eastern supply regions while a west index is used for coal originating from western supply regions. The east index is a function of railroad productivity, the user cost of capital for railroad equipment, and national average diesel fuel price. The user cost of capital for railroad equipment is calculated from the producer price index (PPI) for railroad equipment, and accounts for the opportunity cost of money used to purchase equipment, depreciation occurring as a result of use of the equipment (assumed at 10 percent), less any capital gain associated with the worth of the equipment. In calculating the user cost of capital, three percentage points are added to the cost of borrowing in order to account for the possibility that greenhouse gas emissions may be regulated in the future. The west index is a function of railroad productivity, investment, and the western share of national coal consumption. The indices are universally applied to all domestic coal transportation movements within the CMM. In the AEO2012 Reference case, eastern coal transportation rates are projected to be 4 percent higher in 2035 and western rates in 2035 are projected to be the same as in 2010.
152 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Coal Market Module Figure 11. Coal Supply Regions Source: U.S. Energy Information Administration, Office of Energy Analysis U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 153
Coal Market Module Figure 12. Coal Demand Regions Source: U.S. Energy Information Administration, Office of Energy Analysis For the projection period, the explanatory variables are assumed to have varying impacts on the calculation of the indices.
For the west, investment is the analogous variable to the user cost of capital of railroad equipment. The investment value and the PPI for rail equipment, which is used to derive the user cost of capital increase with an increase in national ton-miles (total tons of coal shipped multiplied by the average distance). Increases in investment (west) or the user cost of capital for railroad equipment (east) cause projected transportation rates to increase. For both the east and the west, any related "nancial savings due to productivity improvements are assumed to be retained by the railroads and are not passed on to shippers in the form of lower transportation rates. For that reason, productivity is held "at for the projection period for both regions. For the east for the projection period, diesel fuel is removed from the equation in order to avoid double-counting the in"uence of diesel fuel costs with the impact of the fuel surcharge program. The transportation rate indices for seven AEO2012 cases are shown in Table 12.2.
154 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Coal Market Module Table 12.2. Transportation rate multipliers constant dollar index, 2010=1.000 Scenario Region: 2010 2015 2020 2025 2030 2035 Reference Case East 1.000 1.0317 1.0672 1.0405 1.0333 1.0435 West 1.000 0.9488 0.9625 0.9930 0.9923 0.9991 High Oil Price East 1.000 1.0204 1.0645 1.0339 1.0422 1.0404 West 1.000 0.9343 0.9483 0.9935 1.0118 1.0408 Low Oil Price East 1.000 1.0277 1.0567 1.0356 1.0222 1.0299 West 1.000 0.9591 0.9750 1.0086 1.0107 1.0105 High Economic Growth East 1.000 1.0299 1.0581 1.0245 1.0338 1.0289 West 1.000 0.9566 0.9752 1.0047 1.0125 1.0157 Low Economic Growth East 1.000 1.0298 1.0999 1.0759 1.0721 1.0829 West 1.000 0.9419 0.9429 0.9680 0.9692 0.9700 High Coal Cost East 1.000 1.0700 1.1700 1.2000 1.2400 1.3000 West 1.000 0.9900 1.0500 1.1300 1.1900 1.2500 Low Coal Cost East 1.000 0.9900 0.9700 0.9000 0.8300 0.7800 West 1.000 0.9100 0.8700 0.8500 0.8000 0.7500 Source: Projections: U.S. Energy Information Administration, National Energy Modeling System runs REF2012.D020112C, HP2012.D022112A, LP2012.
D022112A, HM2012.D022412A, LM2012.D022412A, HCCST12.D031312A, LCCST12.D031312A. Based on methodology described in Coal Market Module of the National Energy Modeling System 2012, DOE/EIA-M066(2012) (Washington, DC, 2012).
Major coal rail carriers have implemented fuel surcharge programs in which higher transportation fuel costs have been passed on to shippers. While the programs vary in their design, the Surface Transportation Board (STB), the regulatory body with limited authority to oversee rate disputes, recommended that the railroads agree to develop some consistencies among their disparate programs and likewise recommended closely linking the charges to actual fuel use. The STB cited the use of a mileage-based program as one means to more closely estimate actual fuel expenses.
For AEO2012, representation of a fuel surcharge program is included in the coal transportation costs. For the west, the methodology is based on BNSF Railway Companys mileage-based program. The surcharge becomes effective when the projected nominal distillate price to the transportation sector exceeds $1.25 per gallon. For every $0.06 per gallon increase above $1.25, a $0.01 per carload mile is charged. For the east, the methodology is based on CSX Transportations mileage-based program. The surcharge becomes effective when the projected nominal distillate price to the transportation sector exceeds
$2.00 per gallon. For every $0.04 per gallon increase above $2.00, a $0.01 per carload mile is charged. The number of tons per carload and the number of miles vary with each supply and demand region combination and are a pre-determined model input.
The "nal calculated surcharge (in constant dollars per ton) is added to the escalator-adjusted transportation rate. For every projection year, it is assumed that 100 percent of all coal shipments are subject to the surcharge program.
Coal contracts in the CMM represent a minimum quantity of a speci"c electricity coal demand that must be met by a unique coal supply source prior to consideration of any alternative sources of supply. Base-year (2010) coal contracts between coal producers and electricity generators are estimated on the basis of receipts data reported by generators on the EIA-923, Power Plant Operations Report. Coal contracts are speci"ed by CMM supply region, coal type, demand region, and whether or not a unit has "ue gas desulfurization equipment. Coal contract quantities are reduced over time on the basis of contract duration data from information reported on the Form EIA-923, Power Plant Operations Report, historical patterns of coal use, and information obtained from various coal and electric power industry publications and reports.
Electric generation demand received by the CMM is subdivided into coal groups representing demands for different sulfur and thermal heat content categories. This process allows the CMM to determine the economically optimal blend of different coals to minimize delivered cost, while meeting emissions requirements. Similarly, nongeneration demands are subdivided into subsectors with their own coal groups to ensure that, for example, lignite is not used to meet a coking coal demand.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 155
Coal Market Module Coal-to-liquids (CTL) facilities are assumed to be economic when low-sulfur distillate prices reach high enough levels.
These plants are assumed to be co-production facilities with generation capacity of 845 MW(300 MW for the grid and 545 MW to support the conversion process) and the capability of producing 50,000 barrels of liquid fuels per day. The technology assumed is similar to an integrated gasi"cation combined cycle, "rst converting the coal feedstock to gas, and then subsequently converting the syngas to liquid hydrocarbons using the Fisher-Tropsch process. Of the total amount of coal consumed at each plant, 46 percent of the energy input is retained in the product with the remaining energy used for conversion and for the production of power sold to the grid. Beginning with AEO2010, coal-biomass-to-liquids (CBTL) capability was incorporated into the NEMS structure. For AEO2012, these facilities are assumed to have a generating capacity of 602MW (150 MW for the grid and 452 MW to support the conversion process) and the capability of producing 30,000 barrels of liquid fuels per day. Eighty percent of the energy input is derived from coal with the remaining 20 percent derived from biomass. CTL and CBTL facilities produce paraffinic naptha used in plastics production and blendable naptha used in motor gasoliine (together about 43 percent of the total by volume) and distillate fuel oil (about 57 percent).
Coal imports and exports Coal imports and exports are modeled as part of the CMMs linear program that provides annual projections of U.S. steam and metallurgical coal exports, in the context of world coal trade. The linear program determines the pattern of world coal trade "ows that minimize the production and transportation costs of meeting U.S. import demand and a pre-speci"ed set of regional world coal import demands. It does this subject to constraints on export capacity and trade "ows.
The key assumptions underlying coal export modeling are:
Coal buyers (importing regions) tend to spread their purchases among several suppliers in order to reduce the impact of potential supply disruptions, even though this may add to their purchase costs. Similarly, producers choose not to rely on any one buyer and instead endeavor to diversify their sales.
Coking coal is treated as homogeneous. The model does not address quality parameters that de"ne coking coals. The values of these quality parameters are de"ned within small ranges and affect world coking coal "ows very little.
Data inputs for coal trade modeling:
World steam and metallurgical coal import demands for the AEO2012 cases are shown in Tables 12.3 and 12.4. U.S. coal exports are determined, in part, by these estimates of world coal import demand.
Step-function coal export supply curves for all non-U.S. supply regions. The curves provide estimates of export prices per metric ton, inclusive of minemouth and inland freight costs, as well as the capacities for each of the supply steps.
Ocean transportation rates (in dollars per metric ton) for feasible coal shipments between international supply regions and international demand regions. The rates take into account typical vessel sizes and route distances in thousands of nautical miles between supply and demand regions.
Coal quality Each year the values of base year coal production, heat, sulfur and mercury content and carbon dioxide emissions for each coal source in CMM are calibrated to survey data. Surveys used for this purpose are the Form EIA-923, a survey of the origin, cost and quality of fossil fuels delivered to generating facilities, and the Form EIA-5, which records the origin, cost and quality of coal delivered to domestic industrial consumers. Estimates of coal quality for the export and residential/commercial sectors are made using the survey data for coal delivered to coking coal and industrial steam coal consumers. Mercury content data for coal by supply region and coal type, in units of pounds of Mercury per trillion Btu, shown in Table 71, were derived from shipment-level data reported by electricity generators to the Environmental Protection Agency in its 1999 Information Collection Request.
Carbon dioxide emission factors for each coal type are shown in Table 12.5 in pounds of carbon dioxide emitted per million Btu
[4].
The CMM projects steam and metallurgical coal trade "ows from 17 coal-exporting regions of the world to 20 import regions for three coal types (coking, bituminous steam, and subbituminous). It includes "ve U.S. export regions and four U.S. import regions.
156 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Coal Market Module Table 12.3. World steam coal import demand by import region million metric tons of coal equivalent 2010 2015 2020 2025 2030 2035 The Americas 37.8 33.7 45.1 60.6 55.1 64.4 3
United States 13.9 11.2 22.1 35.6 26.6 28.3 Canada 7.9 3.1 2.8 2.9 2.9 2.9 Mexico 4.0 4.7 4.8 5.3 5.9 8.3 South America 12.0 14.8 15.4 16.8 19.7 24.9 Europe 122.4 173.1 177.3 175.9 174.5 174.4 Scandinavia 7.8 7.4 6.5 5.8 5.0 4.5 U.K./Ireland 16.8 29.9 29.0 29.0 30.3 31.7 Germany/Austria 28.9 38.8 38.5 37.5 36.6 35.6 Other NW Europe 20.5 22.8 22.1 20.8 20.0 19.2 Iberia 8.5 17.1 18.0 17.9 17.6 16.3 Italy 12.4 20.3 25.3 27.1 27.1 27.1 Med/E Europe 27.5 36.8 37.9 37.8 37.9 40.0 Asia 437.6 474.7 500.6 542.6 596.8 644.1 Japan 89.8 88.8 83.1 79.7 79.6 76.7 East Asia 126.5 128.2 129.6 131.8 140.3 150.1 China/Hong Kong 114.5 134.2 144.5 168.0 189.8 203.9 ASEAN 40.0 44.5 52.4 61.5 69.1 77.2 Indian Sub 66.8 79.0 91.0 101.6 118.0 136.2 TOTAL 597.8 681.5 723.0 779.1 826.4 882.9 1
Import Regions: South America: Argentina, Brazil, Chile, Puerto Rico; Scandinavia: Denmark, Finland, Norway, Sweden; Other NW Europe: Belgium, France, Luxembourg, Netherlands; Iberia: Portugal, Spain; Med/E Europe: Algeria, Bulgaria, Croatia, Egypt, Greece, Israel, Malta, Morocco, Romania, Tunisia, Turkey; East Asia: North Korea, South Korea, Taiwan; ASEAN: Malaysia, Philippines, Thailand; Indian Sub: Bangladesh, India, Iran, Pakistan, Sri Lanka.
2 The base year of the world trade projection for coal is 2010.
3 Excludes imports to Puerto Rico and the U.S. Virgin Islands.
Notes: One metric ton of coal equivalent equals 27.78 million Btu. Totals may not equal sum of components due to independent rounding.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 157
Coal Market Module Table 12.4. World metallurgical coal import demand by import region million metric tons of coal equivalent 2010 2015 2020 2025 2030 2035 The Americas 20.0 30.3 35.4 43.5 54.0 67.3 United States 1.3 1.3 1.3 1.3 1.3 1.3 Canada 3.2 3.2 3.2 3.1 3.0 2.9 Mexico 1.0 1.1 1.1 1.1 1.1 1.1 South America 14.5 24.6 29.8 38.0 48.6 62.0 Europe 59.4 61.3 61.7 61.5 61.5 61.4 Scandinavia 3.2 2.4 2.7 2.7 2.7 2.7 U.K./Ireland 6.7 7.3 7.3 7.3 7.3 7.3 Germany/Austria 12.2 11.4 11.4 11.3 11.3 11.3 Other NW Europe 13.7 14.9 14.7 14.5 14.4 14.3 Iberia 3.5 4.0 3.9 3.9 3.8 3.6 Italy 6.8 7.4 7.4 7.3 7.3 7.3 Med/E Europe 13.3 13.9 14.3 14.5 14.7 14.9 Asia 186.2 201.2 214.6 228.3 232.4 239.7 Japan 79.3 77.4 74.5 70.6 63.8 60.9 East Asia 34.9 36.0 37.1 38.3 39.5 40.6 China/Hong Kong 36.7 42.7 44.1 46.6 48.6 50.9 4
ASEAN 0.0 0.0 0.0 0.0 0.0 0.0 Indian Sub 35.3 45.1 58.9 72.8 80.5 87.3 TOTAL 265.6 292.8 311.7 333.3 347.9 368.4 1
Import Regions: South America: Argentina, Brazil, Chile, Puerto Rico; Scandinavia: Denmark, Finland, Norway, Sweden; Other NW Europe: Belgium, France, Luxembourg, Netherlands; Iberia: Portugal, Spain; Med/E Europe: Algeria, Bulgaria, Croatia, Egypt, Greece, Israel, Malta, Morocco, Romania, Tunisia, Turkey; East Asia: North Korea, South Korea, Taiwan; ASEAN: Malaysia, Philippines, Thailand; Indian Sub: Bangladesh, India, Iran, Pakistan, Sri Lanka.
2 The base year of the world trade projection for coal is 2010.
3 Excludes imports to Puerto Rico and the U.S. Virgin Islands.
4 Malaysia, Phillipines, and Thailand are not expected to import signi"cant amounts of metallurgical coal in the projection.
Notes: One metric ton of coal equivalent equals 27.78 million Btu. Totals may not equal sum of components due to independent rounding.
Legislation and regulations The AEO2012 is based on current laws and regulations in effect before October 31, 2011 with two important exceptions. Because of their signi"cance to electricity and coal markets, the Mercury Air Toxics Standard (MATS), "nalized in December 2011, is included in the "nal release of the AEO2012 Reference case, and the Cross State Air Pollution Rule (CSAPR) (though stayed by the courts in December 2011) is also included.
MATS sets emissions limits for mercury, other heavy metals, and acid gases from coal and oil power plants that are 25 MW or greater. CSASPR was "nalized in July 2011 and sets more stringent emission limits for 28 States for sulfur dioxide and nitrogen oxides. CSASPR and MATS are fully in place by 2014 and 2015, respectively.
158 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Coal Market Module Table 12.5. Production, heat content, sulfur, mercury and carbon dioxide emission factors by coal type and region 2010 Heat Content Sulfur Mercury Production (Million Btu Content Content CO2 Coal Rank and Sulfur (Million per Short (Pounds Per (Pounds per (Pounds Per Coal Supply Region States Level Mine Type short Tons Ton) Million Btu) Trillion Btu) Million Btu)
PA, OH, MD, Northern Appalachia WV (North) Metallurgical Underground 14.5 26.30 0.76 N/A 204.7 Mid-Sulfur Bituminous All 40.2 25.15 1.32 11.17 204.7 High-Sulfur Bituminous All 74.9 24.70 2.67 11.67 204.7 Waste Coal (Gob and Culm) Surface 13.9 11.76 3.79 63.9 204.7 KY (East), WV (South), VA, TN Central Appalachia (North) Metallurgical Underground 50.8 26.30 0.68 N/A 206.4 Low-Sulfur Bituminous All 17.2 24.76 0.54 5.61 206.4 Mid-Sulfur Bituminous All 118.4 24.77 0.91 7.58 206.4 Southern Appalachia AL, TN (South) Metallurgical Underground 10.7 26.30 0.57 N/A 204.7 Low-Sulfur Bituminous All 0.4 25.21 0.49 3.87 204.7 Mid-Sulfur Bituminous All 9.3 24.28 1.25 10.15 204.7 IL, IN, KY(West), Mid-Sulfur East Interior MS Bituminous All 11.8 22.65 1.17 5.6 203.1 High-Sulfur Bituminous All 94.0 22.89 2.57 6.35 203.1 Mid-Sulfur Lignite Surface 4.0 10.39 0.92 14.11 216.5 IA, MO, KS, AR, High-Sulfur West Interior OK, TX (Bit) Bituminous Surface 1.6 21.56 1.89 21.55 202.8 Gulf Lignite TX (Lig), LA Mid-Sulfur Lignite Surface 31.2 13.47 1.18 14.11 212.6 High-Sulfur Lignite Surface 13.8 12.24 2.59 15.28 212.6 Dakota Lignite ND, MT (Lig) Mid-Sulfur Lignite Surface 29.3 13.23 1.17 8.38 219.3 Low-Sulfur Western Montana MT (Sub) Subbituminous Underground 4.4 20.19 0.44 5.06 215.5 Low-Sulfur Subbituminous Surface 22.7 18.36 0.38 5.06 215.5 Mid-Sulfur Subbituminous Surface 17.3 17.06 0.79 5.47 215.5 WY (Northern Powder River Low-Sulfur Northern Wyoming Basin) Subbituminous Surface 167.6 16.82 0.37 7.08 214.3 Mid-Sulfur Subbituminous Surface 2.9 16.17 0.75 7.55 214.3 WY (Southern Powder River Low-Sulfur Southern Wyoming Basin Subbituminous Surface 257.9 17.60 0.30 5.22 214.3 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 159
Coal Market Module Table 12.5. Production, heat content, sulfur, mercury and carbon dioxide emission factors by coal type and region (cont) 2010 Heat Content Sulfur Mercury Production (Million Btu Content Content CO2 Coal Rank and Sulfur (Million per Short (Pounds Per (Pounds per (Pounds Per Coal Supply Region States Level Mine Type short Tons Ton) Million Btu) Trillion Btu) Million Btu)
WY (Other basins, excluding Powder River Low-Sulfur Western Wyoming Basin Subbituminous Underground 3.8 18.64 0.64 2.19 214.3 Low-Sulfur Subbituminous Surface 4.1 19.04 0.62 4.06 214.3 Mid-Sulfur Subbituminous Surface 6.2 19.34 0.89 4.35 214.3 Rocky Mountain CO, UT Metallurgical Underground -- 26.30 0.52 N/A 209.6 Low-Sulfur Bituminous Underground 39.4 22.85 0.48 3.82 209.6 Low-Sulfur Subbituminous Surface 5.1 19.94 0.43 2.04 212.8 Low-Sulfur Southwest AZ, NM Bituminous Surface 7.8 21.64 0.58 4.66 207.1 Mid-Sulfur Subbituminous Surface 16.1 17.80 1.01 7.18 209.2 Mid-Sulfur Bituminous Underground 4.9 19.16 0.70 7.18 207.1 Low-Sulfur Northwest WA, AK Subbituminous Surface 2.2 16.12 0.31 6.99 216.1
--indicates zero production in 2010.
N/A = not available.
Source: U.S. Energy Information Administration, Form EIA-3, Quarterly Coal Consumption and Quality Report Manufacturing and Transformation/Processing Coal Plants and Commercial and Institutional Coal Users; Form EIA-5, Quarterly Coal Consumption and Quality Report, Coke Plants; Form EIA-7A, Coal Production and Preparation Report, and Form EIA-923, Power Plant Operations Report. U.S. Department of Commerce, Bureau of the Census, Monthly Report EM-545. U.S. Environmental Protection Agency, Emission Standards Division, Information Collection Request for Electric Utility Steam Generating Unit, Mercury Emissions Information Collection Effort (Research Triangle Park, NC, 1999). U.S. Environmental Protection Agency, ANNEX 2 Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion, Table A-38, web site http://epa.gov/climatechange/emissions/downloads11/US-GHG-Inventory-2011-Annex-2.pdf.
The Energy Improvement and Extension Act of 2008 (EIEA) and Title IV, under Energy and Water Development, of the American Recovery and Revitalization Act of 2009 (ARRA), together, are assumed to result in 1 gigawatt of advanced coal-"red capacity with carbon capture and sequestration by 2017.
EIEA was passed in October 2008 as part of the Emergency Economic Stabilization Act of 2008. Subtitle B provides investment tax credits for various projects sequestering CO2. Subtitle B, which extends the phaseout of payments by coal producers to the Black Lung Disability Trust Fund from 2013 to 2018, is also modeled in the AEO2012.
Title IV under ARRA provides $3.4 billion for additional research and development on fossil energy technologies. This includes
$800 million to fund projects under the Clean Coal Power Initiative (CCPI) program, focusing on projects that capture and sequester greenhouse gases or use captured carbon dioxide for enhanced oil recovery (EOR). The Hydrogen Energy California Project and a new plant to be built by Summit Texas Clean Energy in Texas both include efforts to use captured carbon dioxide for EOR.
Title XVII of the Energy Policy Act of 2005 authorizes loan guarantees for projects that avoid, reduce, or sequester greenhouse gasses. For AEO2012, the 1 gigawatt of advanced coal-"red capacity with carbon capture and sequestration assumed for EIEA and ARRA are also assumed to bene"t from these loan guarantees.
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Coal Market Module Beginning in 2008, electricity generating units of 25 megawatts or greater were required to hold an allowance for each ton of CO2 emitted in nine Northeastern States as part of the Regional Greenhouse Gas Initiative (RGGI). The States currently participating in RGGI include Connecticut, Maine, Maryland, Massachusetts, Rhode Island, Vermont, New York, New Hampshire, and Delaware.
RGGI is modeled in AEO2012 as an emissions reduction for the Central Atlantic region.
California Assembly Bill 32 (AB32), the Global Warming Solution Act of 2006, was incorporated for electricity sector power plants serving California. As modeled, AB32 imposes a limit on power sector CO2 emissions beginning in 2012 and declining at a uniform annual rate through 2020.
EPA issued "nal guidelines to its regional offices for monitoring the compliance of surface coal mining operations in Appalachia, The guidelines relate primarily to the ongoing controversy over use of the mountaintop removal method at a number of surface coal mining operations in Central Appalachia, primarily in southern West Virginia and eastern Kentucky. While the guidelines require a more rigorous review for all new surface coal mines in Appalachia, the EPA indicated that the practice of valley "lls, primarily associated with the mountaintop removal method, is the aspect of Appalachian coal mining that should be most scrutinized. The impact of the EPAs guidelines for surface coal mining operations in Appalachia is represented by downward adjustments to the coal mining productivity assumptions for Central Appalachian surface mines. The revised productivity levels are based on the assumption that average productivity for surface mining operations in Central Appalachia will decline gradually toward the productivity levels for smaller surface mines in the region as a result of the more restrictive guidelines for overburden management at large mountaintop mining operations.
Coal alternative cases Coal Cost cases In the Reference case, coal mine labor productivity is assumed to decline on average by 1.5 percent per year through 2035 ,miner wage rates increase by about 1.0 percent per year, and mine equipment costs remain constant in 2010 dollars. Eastern and Western transportation rates are 4 percent higher and "at, respectively, in 2035 compared to 2010. In two alternative coal cost cases, productivity, average miner wages, equipment cost, and transportation rate assumptions were modi"ed for 2012 through 2035 in order to examine the impacts on U.S. coal supply, demand, distribution and prices.
In the Low Mining Cost case, coal mine labor productivity is assumed to increase at an average rate of 4.7 percent per year through 2035. Coal mining wages at the regional level are assumed to remain constant in 2035 relative to 2010. Mine equipment costs and other mine supply costs are all assumed to be about 21 percent lower by 2035 in real terms in the Low Coal Cost case. Coal transportation rates, excluding the impact of fuel surcharges, are assumed to be 25 percent lower by 2035.
In the High Mining Cost case, coal mine labor productivity is assumed to decline at an average rate of 4.6 percent per year through 2035. Coal mining wages increase by about 1.9 percent per year. Mine equipment costs, and other mine supply costs are assumed to be about 27 percent higher by 2035. Compared to the Reference case, coal transportation rates are assumed to be 25 percent higher by 2035. The low and high coal cost cases represent fully integrated NEMS runs, with feedback from the Macroeconomic Activity, International, supply, conversion, and end-use demand modules.
No Greenhouse Gas Concern case In the Reference case, to re"ect the market reaction to potential future GHG regulation, a 3-percentage-point increase in the cost of capital for investments in new coal-"red power plants without carbon capture and sequestration technology and new coal-to-liquids plants is assumed. These assumptions affect cost evaluations for the construction of new capacity but not the actual operating costs for new existing plants. This adjustment was "rst implemented for AEO2009. For AEO2012, a 3-percentage-point increase in the cost of capital for investments in retro"ts at existing coal plants is also applied for emission control equipment (excluding CCS).
The No GHG concern case excludes the 3-percentage point increase in the cost of capital.
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Coal Market Module Notes and sources
[1] Energy Information Administration, The U.S. Coal Industry, 1970-1990: Two Decades of Change, DOE/EIA-0559, (Washington, DC, November 1992).
[2] Stanley C. Suboleski, et.al., Central Appalachia: Coal Mine Productivity and Expansion, Electric Power Research Institute, EPRI IE-7117, (September 1991).
[3] The estimated cost of switching to subbituminous coal, $0.10 per million Btu (2000 dollars), was derived by Energy Ventures Analysis, Inc. and was recommended for use in the CMM as part of an Independent Expert Review of the Annual Energy Outlook 2002s Powder River Basin production and transportation rates. Barbaro, Ralph and Seth Schwartz. Review of the Annual Energy Outlook 2002 Reference Case Forecast for PRB Coal, prepared for the Energy Information Administration (Arlington, VA: Energy Ventures Analysis, Inc., August 2002).
[4] U.S. Environmental Protection Agency, Climate ChangeRegulatory Initiative: Greenhouse Gas Reporting Program, website www.epa.gov/climatechange/emissions/
162 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Renewable Fuels Module THIS PAGE INTENTIONALLY LEFT BLANK Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources: biomass, geothermal, conventional hydroelectricity, land"ll gas, solar thermal, solar photovoltaics, and wind [1].
Some renewables, such as land"ll gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Commercial market penetration of renewable technologies varies widely. Hydroelectric power, one of the oldest electric generation technologies, accounts for roughly 6 percent of electric power generation; newer power systems using biomass, geothermal, LFG, solar, or wind energy contribute a combined 4 percent.
The submodules of the RFM interact primarily with the Electricity Market Module (EMM). Because of the high level of integration with the EMM, the "nal outputs (levels of consumption and market penetration over time) for renewable energy technologies are largely dependent upon the EMM. Because some types of biomass fuel can be used for either electricity generation or for the production of liquid fuels, such as ethanol, there is also some interaction with the Petroleum Market Module (PMM), which contains additional representation of some biomass feedstocks that are used primarily for liquid fuels production.
Projections for residential and commercial grid-connected photovoltaic systems are developed in the end-use demand modules and not in the RFM; see the Distributed Generation and Combined Heat and Power description in the Commercial Demand Module section of the report.
Key assumptions Nonelectric renewable energy uses In addition to projections for renewable energy used in central station electricity generation, AEO2012 contains projections of nonelectric renewable energy uses for industrial and residential wood consumption, solar residential and commercial hot water heating, biofuels blending in transportation fuels, and residential and commercial geothermal (ground-source) heat pumps. Assumptions for these projections are found in the residential, commercial, industrial, and petroleum marketing module sections of this report. Additional minor renewable energy applications occurring outside energy markets, such as direct solar thermal industrial applications or direct lighting, off-grid electricity generation, and heat from geothermal resources used directly (e.g., district heating and greenhouses) are not included in the projections.
Electric power generation The RFM considers only grid-connected central station electricity generation systems. The RFM submodules that interact with the EMM are the central station grid-connected biomass, geothermal, conventional hydroelectricity, land"ll gas, solar (thermal and photovoltaic), and wind submodules, which provide speci"c data or estimates that characterize the respective resource. A set of technology cost and performance values is provided directly to the EMM and is central to the build and dispatch decisions of the EMM. The technology cost and performance values are summarized in Table 8.2 in the chapter discussing the EMM.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 165
Renewable Fuels Module Capital costs Capital costs for renewable technologies are affected by several factors. Capital costs for technology to exploit some resources, especially geothermal, hydroelectric, and wind power resources, are assumed to be dependent on the quality, accessibility, and/
or other site-speci"c factors in the areas with exploitable resources. These factors can include additional costs associated with reduced resource quality; need to build or upgrade transmission capacity from remote resource areas to load centers; or local impediments to permitting, equipment transport, and construction in good resource areas due to siting issues, inadequate infrastructure, or rough terrain.
Short-term cost adjustment factors increase technology capital costs as a result of a rapid U.S. buildup in a single year, re"ecting limitations on the infrastructure (for example, limits on manufacturing, resource assessment, and construction expertise) to accommodate unexpected demand growth. These factors, which are applied to all new electric generation capacity, are a function of past production rates and are further described in The Electricity Market Module of the National Energy Modeling System:
Model Documentation Report, available at www.eia.gov/analysis/model-documentation.cfm.
Also assumed to affect all new capacity types are costs associated with construction commodities. Through much of the past 10 years, the installed cost for most new plants was observed to increase. Although several factors contributed to this cost escalation, some of which may be more or less important to speci"c types of new capacity, much of the overall cost increase was correlated with increases in the cost of construction materials, such as bulk metals, specialty metals, and concrete. Capital costs are speci"cally linked to the projections for the metals producer price index found in the Macroeconomic Module of NEMS.
Independent of the other two factors, capital costs for all electric generation technologies, including renewable technologies, are assumed to decline as a function of growth in installed capacity for each technology.
For a description of NEMS algorithms lowering generating technologies capital costs as more units enter service (learning),
see Technological Optimism and Learning in the EMM chapter of this report. A detailed description of the RFM is provided in the EIA publication, Renewable Fuels Module of the National Energy Modeling System, Model Documentation 2011, DOE/
EIA-M069(2011) (Washington, DC, 2011).
Solar Electric Submodule
Background
The Solar Electric Submodule currently includes both solar thermal (also referred to as concentrating solar power or CSP) and photovoltaic (PV), technologies. The representative solar thermal technology assumed for cost estimation is a 100-megawatt central-receiver tower without integrated energy storage, while the representative solar PV technology is a 150-megawatt array of "at plate PV modules using single-axis tracting. PV is assumed available in all EMM regions, while CSP is available only in the Western regions with the arid atmospheric conditions that result in the most cost-effective capture of direct sunlight. Cost estimates for both technologies are based on a report by R.W. Beck, Inc. (see www.eia.gov/oiaf/beck_plantcosts). Technology-speci"c performance characteristics are obtained from information provided by the National Renewable Energy Laboratory (NREL).
Assumptions t NEMS represents the Energy Policy Act of 1992 (EPACT92) permanent 10-percent investment tax credit (ITC) for solar electric power generation by tax-paying entities. In addition, the current 30-percent ITC, scheduled to expire at the end of 2016, is also represented to qualifying new capacity installations.
t Existing capacity and planned capacity additions are based on EIA survey data from the Form EIA-860, Annual Electric Generator Report and Form EIA-860M, Monthly Update to the Annual Electric Generator Report. Planned capacity additions under construction or having all regulatory approvals and having an expected completion date prior to the expiration of the 30-percent ITC were included in the models planned capacity additions, according to respondents planned completion dates.
t Capacity factors for solar technologies are assumed to vary by time of day and season of the year, such that nine separate capacity factors are provided for each modeled region, three for time of day and for each of three broad seasonal groups (summer, winter, and spring/fall). Regional capacity factors vary from national averages based on climate and latitude.
t Solar resources are well in excess of conceivable demand for new capacity; energy supplies are considered unlimited within regions (at speci"ed daily, seasonal, and regional capacity factors). Therefore, solar resources are not estimated in NEMS. In the regions where CSP technology is not modeled, the level of direct, normal insolation (the kind needed for that technology) is assumed to be insuf"cient to make that technology commercially viable through the forecast horizon.
166 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Renewable Fuels Module Wind-Electric Power Submodule
Background
Because of limits to windy land areas, wind is considered a "nite resource, so the submodule calculates maximum available capacity by Electricity Market Module Supply Regions. The minimum economically viable average wind speed is about 14 mph, and wind speeds are categorized by annual average wind speed based on a classi"cation system originally from the Paci"c Northwest Laboratory. The RFM tracks wind capacity (megawatts) by resource quality and costs within a region, and moves to the next best wind resource when one category is exhausted. Wind resource data on the amount and quality of wind per EMM region come from the National Renewable Energy Laboratory [2]. The technological performance, cost, and other wind data used in NEMS are derived by EIA from a report by R.W. Beck, Inc. (see www.eia.gov/oiaf/beck_plantcosts/). Maximum wind capacity, capacity factors, and incentives are provided to the EMM for capacity planning and dispatch decisions. These form the basis on which the EMM decides how much power generation capacity is available from wind energy. The fossil-fuel heat rate equivalents for wind are used for energy consumption calculation purposes only.
Assumptions t Only grid-connected (utility and nonutility) generation is included. Projections for distributed wind generation are included in the commercial and residential modules.
t In the wind submodule, wind supply costs are affected by three modeling measures addressing: (1) average wind speed, (2) distance from existing transmission lines, and (3) resource degradation, transmission network upgrade costs, and market factors.
t Available wind resource is reduced by excluding all windy lands not suited for the installation of wind turbines because of:
excessive terrain slope (greater than 20 percent); reservation of land for non-intrusive uses (such as National Parks, wildlife refuges, and so forth); inherent incompatibility with existing land uses (such as urban areas, areas surrounding airports and water bodies, including offshore locations); insuf"cient continguous windy land to support a viable wind plant (less than 5 square kilometers of windy land in a 100-square-kilometer area). Half of the wind resource located on military reservations, U.S. Forest Service land, state forested land, and all non-ridge-crest forest areas are excluded from the available resource base to account for the uncertain ability to site projects at such locations. These assumptions are detailed in the Draft Final Report to EIA titled, Incorporation of Existing Validated Wind Data into NEMS, November 2003.
t Capital costs for wind technologies are assumed to increase in response to (1) declining natural resource quality, such as terrain slope, terrain roughness, terrain accessibility, wind turbulence, wind variability, or other natural resource factors, as the best sites are utilized, (2) increasing cost of upgrading existing local and network distribution and transmission lines to accommodate growing quantities of remote wind power, and (3) market conditions, such as the increasing costs of alternative land uses, including aesthetic or environmental reasons. Capital costs are left unchanged for some initial share, then increased by 10, 25, 50 percent, and "nally 100 percent, to represent the aggregation of these factors.
t Proportions of total wind resources in each category vary by EMM region. For all EMM regions combined, about 1 percent of windy land (107 GW of 11,600 GW in total resource) is available with no cost increase, 3.4 percent (390 GW) is available with a 10 percent cost increase, 2 percent (240 GW) is available with a 25-percent cost increase, and over 90 percent is available with a 50- or 100-percent cost increase.
t Depending on the EMM region, the cost of competing fuels, and other factors, wind plants can be built to meet system capacity requirements or as a fuel saver to displace generation from existing capacity. For wind to penetrate as a fuel saver, its total capital and "xed operations and maintenance costs minus applicable subsidies must be less than the variable operating costs, including fuel, of the existing (non-wind) capacity. When competing in the new capacity market, wind is assigned a capacity credit that declines based on its estimated contribution to regional reliability requirements.
t Because of downwind turbulence and other aerodynamic effects, the model assumes an average spacing between turbine rows of 5 rotor diameters and a lateral spacing between turbines of 10 rotor diameters. This spacing requirement determines the amount of power that can be generated from wind resources, about 6.5 megawatts per square kilometer of windy land, and is factored into requests for generating capacity by the EMM.
t Capacity factors are assumed to increase to 46 percent in the best wind class resulting from taller towers, more reliable equipment, and advanced technologies. Capacity factors for each wind class are calculated as a function of overall wind market growth. The capacity factors are assumed to be limited to about 48 percent for a typical Class 6 site. As better wind resources are depleted, capacity factors are assumed to go down, corresponding with the use of less desirable sites. By 2035, the typical wind plant build will have a somewhat lower capacity factor than those found in the best wind resource areas.
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Renewable Fuels Module t AEO2012 does not allow plants constructed after 2012 to claim the federal Production Tax Credit (PTC), a 2.2-cent-per-kilowatt-hour tax incentive for wind that is set to expire on December 31, 2012 for wind only. Wind plants are assumed to depreciate capital expenses using the Modi"ed Accelerated Cost Recovery Schedule with a 5-year tax life.
Offshore wind resources are represented as a separate technology from onshore wind resources. Offshore resources are modeled with a similar model structure as onshore wind. However, because of the unique challenges of offshore construction and the somewhat different resource quality, the assumptions with regard to capital cost, learning-by-doing cost reductions, and variation of resource exploitation costs and performance differ signi"cantly from onshore wind.
t Like onshore resources, offshore resources are assumed to have an upwardly sloping supply curve, in part in"uenced by the same factors that determine the onshore supply curve (such as distance to load centers, environmental or aesthetic concerns, variable terrain/seabed) but also explicitly by water depth.
t Because of the more dif"cult maintenance challenge offshore, performance for a given annual average wind power density level is assumed to be somewhat reduced by reduced turbine availability. Offsetting this, however, is the availability of resource areas with higher overall power density than is assumed available onshore. Capacity factors for offshore are limited to be about 50 percent for a Class 7 site.
t Cost reductions in the offshore technology result in part from learning reductions in onshore wind technology as well as from cost reductions unique to offshore installations, such as foundation design and construction techniques. Because offshore technology is signi"cantly less mature than onshore wind technology, offshore-speci"c technology learning occurs at a somewhat faster rate than on-shore technology. A technological optimism factor (see EMM documentation: www.eia.gov/
analysis/model-documentation.cfm) is included for offshore wind to account for the substantial cost of establishing the unique construction infrastructure required for this technology.
Geothermal-Electric Power Submodule
Background
Beginning in AEO2011, all geothermal supply curve data came from the National Renewable Energy Laboratorys updated U.S.
geothermal supply curve assessment. The report, released in February 2010, assigns cost estimates to the U.S. Geological Surveys (USGS) 2008 geothermal resource assessment. Some data from the 2006 report, The Future of Geothermal Energy, prepared by the Massachusetts Institute of Technology, was also incorporated into the NREL report; however, this would be more relevant to deep, dry, and unknown geothermal resources, something which EIA did not include in its supply curve. NREL took the USGS data and used the Geothermal Electricity Technology Evaluation Model (GETEM), an Excel-based techno-economic systems analysis tool, to estimate the costs [3]. Only resources with temperatures above 110 degrees Celsius were considered. There are approximately 125 of these known, hydrothermal resources which EIA used in its supply curve. Each of these sites also has what NREL classi"ed as near-"eld enhanced geothermal energy system potential which are in areas around the identi"ed site that lack the permeability of "uids that are present in the hydrothermal potential. Therefore, there are 250 total points on the supply curve since each of the 125 hydrothermal sites has corresponding enhanced geothermal system (EGS) potential.
In the past, EIA cost estimates were broken down into cost-speci"c components. Unfortunately, this level of detal was not available in the NREL data. A site-speci"c capital cost and "xed operations and maintenance cost were provided. Both types of technology, both "ash and binary, are also included with capacity factors ranging from 90 to 95 percent. While the source of the data was changed beginning in AEO2011, the site-by-site matrix input that acts as the supply curve has been retained.
Assumptions t Existing and identi"ed planned capacity data are obtained directly by the EMM from Form EIA-860 and Form EIA-860m.
t The permanent investment tax credit of 10 percent available in all projection years, based on the EPACT, applies to all geothermal capital costs, except through December 2013 when the 2.2-cent production tax credit is available to this technology and is assumed chosen instead.
t Plants are not assumed to retire unless their retirement is reported to EIA. The Geysers units are not assumed to retire but instead are assigned the 35-percent capacity factors reported to EIA re"ecting their reduced performance in recent years.
t Capital and operating costs vary by site and year; values shown in Table 8.2 in the EMM chapter are indicative of those used by EMM for geothermal build and dispatch decisions.
168 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Renewable Fuels Module Biomass Electric Power Submodule
Background
Biomass consumed for electricity generation is modeled in two parts in NEMS. Capacity in the wood products and paper industries, the so-called captive capacity, is included in the industrial sector module as cogeneration. Generation in the electricity sector is represented in the EMM. Fuel costs are calculated in NEMS and passed to EMM, while capital and operating costs and performance characteristics are assumed as shown in Table 8.2. Fuel costs are provided in sets of regional supply schedules.
Projections for ethanol are produced by the Petroleum Market Module (PMM), with the quantities of biomass consumed for ethanol decremented from, and prices obtained from, the EMM regional supply schedules.
Assumptions t Existing and planned capacity data are obtained from Form EIA-860 and Form EIA-860m.
t The conversion technology represented is an 80-MW dedicated combustion plant. The cost estimates for this technology were prepared by R.W. Beck, Inc. for EIA.
t Biomass co-"ring can occur up to a maximum of 15 percent of fuel used in coal-"red generating plants.
Fuel supply schedules are a composite of four fuel types: forestry materials, wood residues, agricultural residues, and energy crops. Feedstock potential from agricultural residues and dedicated energy crops are calculated from a version of the Policy Analysis (POLYSYS) agricultural model that uses the same oil prices as the rest of NEMS. Forestry residues are calculated from inventories conducted by the U.S. Forest Service and Oak Ridge National Laboratory. The forestry materials component is made up of logging residues, rough rotten salvageable dead wood, and excess small pole trees.[4] The wood residue component consists of primary mill residues, silvicultural trimmings, and urban wood such as pallets, construction waste, and demolition debris that are not otherwise used [5]. Agricultural residues are wheat straw, corn stover, and a number of other major agricultural crops [6]. Energy crop data are for hybrid poplar, willow, and switchgrass grown on existing cropland. POLYSYS assumes that the additional cropland needed for energy crops will displace existing pasturelands. The lands in the Conservation Reserve Program are preserved [7]. The maximum amount of resources in each coal region is shown in Table 13.1.
Table 13.1. Maximum U.S. biomass resources, by coal demand region and type in 2035 trillion Btu Urban Wood Coal Demand Waste/Mill Region States Agricultural Sector Forestry Residue Residue 1 (NE) CT, MA, ME, NH, RI, VT 41 115 40 2 (YP) NY, PA, NJ 189 162 88 3 (S1) WV, MD, DC, DE 75 91 37 4 (S2) VA, NC, SC 465 364 58 5 (GF) GA, FL 345 358 87 6 (OH) OH 178 60 37 7 (EN) IN, IL, MI, WI 703 155 81 8 (KT) KY, TN 475 167 43 9 (AM) AL, MS 391 332 43 10 (C1) MN, ND, SD 1272 57 31 11 (C2) IA, NE, MO, KS 2485 77 45 12 (WS) TX, LA, OK, AR 1582 269 86 13 (MT) MT, WY, ID 120 61 26 14 (CU) CO, UT, NV 52 59 51 15 (ZN) AZ, NM 22 73 41 16 (PC) AK, HI, WA, OR, CA 106 239 122 Sources: U.S. Billion-Ton Update (Oak Ridge National Lab, 2011) and the Policy Analysis (POLYSYS) model developed by the University of Tennessees Department of Agricultural Economics.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 169
Renewable Fuels Module J " ""4X-6
Background
Land"ll-gas-to-electricity capacity competes with other technologies using supply curves that are based on the amount of high, low, and very low methane-producing land"lls located in each EMM region. An average cost-of-electricity for each type of land"ll is calculated using gas collection system and electricity generator costs and characteristics developed by EPAs Energy Project Land"ll Gas Utilization Software (E-PLUS) [8] .
Assumptions t Gross domestic product (GDP) and population are used as the drivers in an econometric equation that establishes the supply of land"ll gas.
t Recycling is assumed to account for 50 percent of the waste stream in 2010 (consistent with EPAs recycling goals).
t The waste stream is characterized into three categories: readily, moderately, and slowly decomposable material.
t Emission parameters are the same as those used in calculating historical methane emissions in EIAs Emissions of Greenhouse Gases in the United States 2003 [9] .
t The ratio of high, low, and very low methane production sites to total methane production is calculated from data obtained for 156 operating land"lls contained in the Government Advisory Associates METH2000 database [10] .
t Cost-of-electricity for each site was calculated by assuming each site to be a 100-acre by 50-foot deep land"ll and by applying methane emission factors for high, low, and very low methane emitting wastes.
Conventional hydroelectricity The conventional hydroelectricity submodule represents U.S. potential for new conventional hydroelectric capacity of 1 megawatt or greater from new dams, existing dams without hydroelectricity, and from adding capacity at existing hydroelectric dams.
Summary hydroelectric potential is derived from reported lists of potential new sites assembled from Federal Energy Regulatory Commission (FERC) license applications and other survey information, plus estimates of capital and other costs prepared by the Idaho National Engineering and Environmental Laboratory (INEEL) [11]. Annual performance estimates (capacity factors) were taken from the generally lower but site-speci"c FERC estimates rather than from the general estimates prepared by INEEL, and only sites with estimated costs of 10 cents per kilowatthour or lower are included in the supply. Pumped storage hydro, considered a nonrenewable storage medium for fossil and nuclear power, is not included in the supply; moreover, the supply does not consider offshore or in-stream hydro, efficiency or operational improvements without capital additions, or additional potential from refurbishing existing hydroelectric capacity.
In the hydroelectricity submodule, sites are "rst arrayed by NEMS region from least to highest cost per kilowatthour. For any years capacity decisions, only those hydroelectric sites whose estimated levelized costs per kilowatthour are equal to or less than an EMM-determined avoided cost (the least cost of other technology choices determined in the previous decision cycle) are submitted. Next, the array of below-avoided-cost sites is parceled into three increasing cost groups, with each group characterized by the average capacity-weighted cost and performance of its component sites. Finally, the EMM receives from the conventional hydroelectricity submodule the three increasing-cost quantities of potential capacity for each region, providing the number of megawatts potential along with their capacity-weighted average overnight capital cost, operations and maintenance cost, and average capacity factor. After choosing from the supply, the EMM informs the hydroelectricity submodule, which decrements available regional potential in preparation for the next capacity decision cycle.
Legislation and regulations Renewable electricity tax credits The RFM includes the investment and energy production tax credits codi"ed in the Energy Policy Act of 1992 (EPACT92) as amended. The investment tax credit established by EPACT92 provides a credit to Federal income tax liability worth 10 percent of initial investment cost for a solar, geothermal, or qualifying biomass facility. This credit was raised to 30 percent through 2016 for some solar projects and extended to residential projects. This change is re"ected in the RFM, commercial demand, and residential demand modules. The production tax credit, as established by EPACT92, applied to wind and certain biomass facilities.
As amended, it provides a 2.2-cent tax credit for every kilowatthour of electricity produced for the "rst 10 years of operation for a wind facility constructed by December 31, 2012 or by December 31, 2013 for other eligible facilities. The value of the credit, originally 1.5 cents, is adjusted annually for in"ation. With the various amendments, the production tax credit is available for electricity produced from qualifying geothermal, animal waste, certain small-scale hdroelectric, land"ll gas, municipal solid waste, 170 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Renewable Fuels Module and additional biomass resources. Wind, poultry litter, geothermal, and closed loop [12] biomass resources receive a 2.2-cent tax credit for the "rst 10 years of facility operations. All other renewable resources receive a 1.1 cent (that is, one-half the value of the credit for other resources) tax credit for the "rst 10 years of facility operations. EIA assumes that biomass facilities obtaining the PTC will use open-loop fuels, as closed-loop fuels are assumed to be unavailable and/or too expensive for widespread use during the period that the tax credit is available. The investment and production tax credits are exclusive of one another, and may not both be claimed for the same geothermal facility (which is eligible to receive either).
State RPS programs EIA represents various State-level policies generally referred to as Renewable Portfolio Standards (RPS). These policies vary signi"cantly among States, but typically require the addition of renewable generation to meet a speci"ed share of State-wide generation. Any non-discretionary limitations on meeting the generation or capacity target are modeled to the extent possible.
However, because of the complexity of the various requirements, the regional target aggregation, and nature of some of the limitations, the measurement of compliance is assumed to be approximate.
Regional renewable generation targets were estimated using the renewable generation targets in each State within the region.
In many cases, regional boundaries intersect State boundaries; in these cases State requirements were divided among relevant regions based on sales. Using State-level RPS compliance schedules and preliminary estimates of projected sales growth, EIA estimated the amount of renewable generation required in each State within a region. Required generation in each State was then summed to the regional level for each year, and a regional renewable generation share of total sales was determined, as shown in Table 13.2.
Only targets with established enforcement provisions or established State funding mechanisms were included in the calculation; goals, provisional RPS requirements, or requirements lacking established funding were not included. The California and New York programs require State funding, and these programs are assumed to be complied with only to the extent that State funding allows. Compliance enforcement provisions vary signi"cantly among States and most States have established procedures for waiving compliance through the use of alternative compliance payments, penalty payments, discretionary regulatory waivers, or retail price impact limits. Because of the variety of mechanisms, even within a given electricity market region, these limits are not modeled.
Alternative renewable case Low Renewable Cost case The Low Renewable Cost case examines the effect of reducing technology energy costs by 2035 to 40 percent below Reference case values with an initial reduction of 20 percent.
Because the cost of supply of renewable resources is assumed to increase with increasing utilization (that is, the renewable resource supply curves are upwardly sloping), the cost reduction is achieved by targeting the reduction on the marginal unit of supply for each technology in 2035 for the Reference case (that is, the next resource available to be utilized in the Reference case in 2035). This has the effect of reducing costs for the entire supply (that is, shifting the supply curve downward by 40 percent).
As a result of the overall reduction in costs, more supply may be utilized, and a unit from higher on the supply curve may become the marginal unit of supply. Thus, the actual market-clearing cost-of-energy for a given renewable technology may not differ by much from the Reference case, although that resource contributes more energy supply than in the Reference case. These cost reductions are achieved gradually and are only fully realized by 2035.
For wind, biomass, geothermal, and solar technologies, this cost reduction is achieved by a reduction in overnight capital costs sufficient to achieve the targeted reduction in cost-of-energy. For geothermal, the capital cost of the lowest-cost site available in the year 2011 is reduced such that if it were available for construction in 2035, it would have a 40 percent lower cost-of-energy in the Low Renewable Cost case than the cost-of-energy it would have in 2035 were it available for construction in the Reference case. Biomass prices are assumed to be reduced 40 percent by 2035 for a given quantity of fuel supplied. Other assumptions within NEMS are unchanged from the Reference case.
For the Low Renewable Cost case, demand-side improvements are also assumed in the renewable energy technology options of residential demand, commercial demand, industrial demand, and PMM modules. Details on these assumptions can be found in the corresponding sections of this report.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 171
Renewable Fuels Module Table 13.2. Aggregate regional renewable portfolio standard requirements (percentage share of total values)
Region1 2015 2025 2035 Texas Reliability Entity 4.2% 4.2% 4.2%
Midwest Reliability Council - East 10.0% 10.0% 10.0%
Midwest Reliability Council - West 4.9% 7.3% 7.3%
Northeast Power Coordinating Council - Northeast 9.5% 13.8% 13.8%
Northeast Power Coordinating Council - NYC/Westchester 25.7% 25.7% 25.7%
Northeast Power Coordinating Council - Long Island 25.7% 25.7% 25.7%
Northeast Power Coordinating Council - Upstate NY 25.7% 25.7% 25.7%
Reliability First Corporation - East 9.5% 14.4% 14.5%
Reliability First Corporation - Michigan 10.0% 10.0% 10.0%
Reliability First Corporation - West 4.3% 9.6% 9.6%
SERC Reliability Corporation - Delta 0.6% 0.7% 0.7%
SERC Reliability Corporation - Gateway 6.6% 15.7% 15.7%
SERC Reliability Corporation - Virginia/Carolina 2.6% 5.2% 5.2%
Southwest Power Pool - North 7.0% 15.2% 15.3%
Southwest Power Pool - South 1.3% 1.6% 1.6%
Western Electricity Coordinating Council - Southwest 6.3% 10.0% 10.0%
Western Electricity Coordinating Council - California 22.5% 33.0% 33.0%
Western Electricity Coordinating Council - Northwest 5.1% 11.4% 11.4%
Western Electricity Coordinating Council - Rockies 9.9% 14.8% 18.5%
1 See chapter on the Electricity Market Module for a map of the electricity market module supply regions.
172 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Renewable Fuels Module Notes and sources
[1] For a comprehensive description of each submodule, see U. S. Energy Information Administration, Office of Integrated Analysis and Forecasting, Model Documentation, Renewable Fuels Module of the National Energy Modeling System, DOE/EIA-M069(2011), (Washington, DC, August 2011).
[2] Revising the Long Term Multipliers in NEMS: Quantifying the Incremental Transmission Costs Due to Wind Power, Report to EIA from Princeton Energy Resources International, LLC. May 2007.
[3] The one exception applies to the Salton Sea resource area. For that site, EIA used cost estimates provided by R.W.
Beck, Inc. rather than NREL.
[4] United States Department of Agriculture, U.S. Forest Service, Forest Resources of the United States, 1992, General Technical Report RM-234, (Fort Collins CO, June 1994).
[5] Antares Group Inc., Biomass Residue Supply Curves for the U.S., prepared for the National Renewable Energy Laboratory, June 1999.
[6] Walsh, M.E., et.al., Oak Ridge National Laboratory, The Economic Impacts of Bioenergy Crop Production on U.S.
Agriculture, (Oak Ridge, TN, May 2000), https://bioenergy.ornl.gov/papers/wagin/index.html.
[7] Graham, R.L., et.al., Oak Ridge National Laboratory, The Oak Ridge Energy Crop County Level Database, (Oak Ridge TN, December, 1996).
[8] U.S. Environmental Protection Agency, Atmospheric Pollution Prevention Division, Energy Project Land"ll Gas Utilization Software (E-PLUS) Version 1.0, EPA-430-B-97-006 (Washington, DC, January 1997).
[9] U.S. Energy Information Administration, Emissions of Greenhouse Gases in the United States 2003, DOE/EIA-0573(2003) (Washington, DC, December 2004), www.eia.gov/oiaf/1605/archive/gg04rpt/index.html.
[10] Governmental Advisory Associates, Inc., METH2000 Database, Westport, CT, January 25, 2000.
[11] Douglas G. Hall, Richard T. Hunt, Kelly S. Reeves, and Greg R. Carroll, Idaho National Engineering and Environmental Laboratory, Estimation of Economic Parameters of U.S. Hydropower Resources INEEL/EXT-03-00662 (Idaho Falls, Idaho, June 2003), //hydropower.inel. gov/resourceassessment/index.html.
[12] Closed-loop biomass are crops produced explicitly for energy production. Open-loop biomass are generally wastes or residues that are a byproduct of some other process, such as crops grown for food, forestry, landscaping, or wood milling.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 173
THIS PAGE INTENTIONALLY LEFT BLANK Appendix A: Handling of Federal and selected State legislation and regulation in the AEO
THIS PAGE INTENTIONALLY LEFT BLANK Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis Residential sector A. National Appliance Energy Conservation Requires Secretary of Energy Included for categories Public Law 100-12.
Act of 1987 to set minimum efficiency represented in the AEO standards for 10 appliance residential sector forecast.
categories with periodic updates
- a. Room air conditioners Sets standards for room air Require new purchases of Federal Register Notice conditioners in 2014. room air conditioners to meet of Final Rulemaking.
the standard.
- b. Central air conditioners and heat Sets standards for central air Require new purchases of Federal Register Notice pumps conditioners in 2015. other air conditioners to meet of Final Rulemaking.
the standard.
- c. Water heaters Sets standards for water Require new purchases of Federal Register Notice heaters in 2015. water heaters to meet the of Final Rulemaking.
standard.
- d. Refrigerators and freezers Sets standards for refrigerators Require new purchases of Federal Register Notice and freezers in 2014. refrigerators/freezers to meet of Final Rulemaking.
the standard.
- e. Dishwashers Sets standards for dishwasher Require new purchases of Federal Register Notice in 2010. dishwashers to meet the of Final Rulemaking.
standard.
- f. Fluorescent lamp ballasts Sets standards for "uorescent Require new purchases of Federal Register Notice lamp ballasts in 2005. "uorescent lamp ballasts to of Final Rulemaking.
meet the standard.
- g. Clothes washers Sets standards for clothes Require new purchases of Federal Register Notice washers in 2011. clothes washers to meet the of Final Rulemaking.
standard.
- h. Furnaces Sets standards for furnaces in Require new purchases of Federal Register Notice 2013. furnaces to meet the standard. of Final Rulemaking.
- i. Clothes dryers Sets standards for clothes Require new purchases of Federal Register Notice dryers in 2015. clothes dryers to meet the of Final Rulemaking.
standard.
- j. Boilers Sets standards for boilers in Require new purchases of Federal Register Notice 2012. boilers to meet the standard. of Final Rulemaking.
B. Energy Policy Act of 1992 (EPACT1992) Public Law 102-486
- a. Building codes For the IECC 2006, speci"es Assumes that all States adopt Trend of States whole house efficiency the IECC 2006 code by 2017. adoption to codes, minimums. allowing for lead times for enforcement and builder compliance.
- b. Various lighting types Sets standards for various Require new purchases of Federal Register Notice lightig types in 2012. various lighting types to meet of Final Rulemaking.
the standards.
C. Energy Policy Act of 2005 (EPACT2005) Public Law 109-58.
- a. Torchiere lamp standard Sets standard for torchiere Requires new purchases of Federal Register Notice lamps in 2006. torchiere bulbs to meet the of Final Rulemaking.
standard.
- b. Compact "uorescent lamp standard Sets standard for "uorescent Requires new purchases of Federal Register Notice lamps in 20006. compact "uorescent bulbs to of Final Rulemaking.
meet the standard.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 177
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis
- c. Ceiling fan light kit standard Sets standard for ceiling Reduce lighting electricity Number of ceiling fan fans and ceiling fan light consumption by appropriate shipments and estimated kits in 2007. amount. kWh savings per unit determine overall savings.
- d. Dehumidi"er standard Sets standard for Reduce dehumid"er Number of dehumidi"er dehumidi"ers in 2012. electricity consumption by shipments and estimated appropriate amount. kWh savings per unit determine overall savings.
- e. Energy-efficient equipment tax credit Purchasers of certain Reduce cost of applicable energy-efficient equipment equipment by speci"ed can claim tax credits in amount.
2006 and 2007.
- f. New home tax credit Builders receive $1000 or Reduce shell package cost Cost reductions to
$2000 tax credit if they for these homes by speci"ed consumers are assumed build homes 30 or 50 amount. to be 100 percent of the percent better than code in builders tax credit.
2006 and 2007.
- g. Energy-efficient appliance tax credit Producers of energy- Assume the cost savings are Cost reductions to efficient refrigerators, passed on to the consumer, consumers are assumed dishwashers, and clothes reducing the price of the to be 100 percent of the washers receive tax appliance by the speci"ed producers tax credit.
credits for each unit they amount.
produce that meets certain efficiency speci"cations D. Energy Independence and Security Act of 2007 (EISA 2007) Public Law 110-140.
- a. General service incandescent lamp Require less wattage for Reduce wattage for new Federal Register Notice of standard bulbs in 2012-2014 and bulbs by 28 percent in 2013 Final Rulemaking.
2020. and 67 percent in 2020.
- b. External power supply standard Sets standards for external Reduce external power Number of shipments and power supplies in 2008. supply electricity estimated kWh savings consumption by per unit determine overall appropriate amount. savings.
- c. Manufactured housing code Require manufactured Require that all EISA 2007.
homes to meet latest IECC manufactured homes in 2011. shipped after 2011 meet the IECC 2006 E. Energy Improvement and Extension Act of 2008 (EIEA 2008) Public Law 110-343.
- a. Energy-efficient equipment tax credit Purchasers of certain Reduce the cost of EIEA 2008.
energy-efficient equipment applicable equipment by can claim tax credits speci"ed amount.
through 2016.
- b. Energy-efficient appliance tax credit Producers of energy- Assume the cost savings are Cost reductions to consumer efficient refrigerators, passed on to the consumer, are assumed to be 100 clothes washers, and reducing the price of the percent of the producers tax dishwashers receive tax appliance by the speci"ed credit.
credits for each unit they amount.
produce that meets certain efficiency speci"cations, subject to an annual cap.
178 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis F. American Recovery and Reinvestment Act of 2009 Public Law 111-5.
- a. Energy-efficient equip- Increases cap to $1500 of energy- Reduce the cost of applicable EPACT 2005 and ARRA ment tax credit efficient equipment speci"ed equipment by speci"ed amount. 2009.
under Section C(d) above.
Removes cap for PV, wind, and ground-source heat pumps
- b. Weatherization and State Increases funding for Apply annual funding amount to ARRA 2009.
energy programs weatherization and other existing housing retro"ts. Savings for programs to increase the energy heating and cooling based on $2600 efficiency of existing housing per home investment as speci"ed in stock. weatherization program evaluation.
G. Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act of 2010 Public Law 111-312.
- a. Energy-efficient Extends tax credits for some Reduce the cost of applicable equipment tax credit energy-efficient equipment, equipment by speci"ed amount.
generally to EISA 2007 amounts.
Commercial sector A. National Appliance Energy Requires Secretary of Energy to Included for categories represented Conservation Act of 1987 set minimum efficiency standards in the AEO commercial sector for 10 appliance categories. forecast.
- a. Room air conditioners Current standard of 9.8 EER Federal Register Notice of increasing to 10.9 CEER in 2014. Final Rulemaking.
- b. Other residential-size 10 SEER before 2006 for central air Federal Register Notice of air conditioners (<5.4 conditioning and heat pumps; 13 Final Rulemaking.
tons) SEER in 2006; 14 SEER in 2015.
- c. Fluorescent lamp Current standard of 0.90 power Federal Register Notice of ballasts factor and minimum efficacy factor Final Rulemaking.
for F40 and F96 lamps based on lamp size and wattage, increasing to higher efficacy factor in 2005 that limits purchases to electronic ballasts.
B. Energy Policy Act of 1992 (EPACT92)
- a. Building codes Incorporated in commercial building Based on Science shell assumptions. Efficiency of new Applications International relative to existing shell represented Corporation commercial in shell efficiency indices. Assumes shell indices for 2003 shell efficiency improves 5 and developed for EIA in 2008 7 percent by 2030 for existing and 2011.
buildings and new construction, respectively.
- b. Window labeling Designed to help consumers Incorporated in commercial building Based on Science determine which windows are shell assumptions. Efficiency of new Applications International more energy efficient. relative to existing shell represented Corporation commercial by shell efficiency indices. Assume shell indices for 2003 shell efficiency improves 5 and developed for EIA in 2008 7 percent by 2030 for existing and 2011.
buildings and new construction, respectively.
- c. Commercial furnaces Gas-"red furnaces and boilers: Public Law 102-486:
and boilers Current standard is 0.80% thermal EPACT92. Federal Register efficiency. Oil furnaces and boilers: Notice of Final Rulemaking.
Current standard is 0.81% thermal efficiency for furnaces, 0.83%
thermal efficiency for boilers.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 179
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis
- d. Commercial air Air-cooled air conditioners and heat Public Law 102-486:
conditioners and heat pumps less than 135,000 EPACT92.
pumps Btu: 2001 standard of 8.9 EER.
Air-cooled air conditioners and heat pumps greater than 135,000 Btu:
2001 standard of 8.5 EER.
- e. Commercial water heaters Natural gas and oil: EPACT Public Law 102-486:
standard 0.78-percent thermal EPACT92. Federal Register efficiency increasing to 80-percent Notice of Final Rulemaking.
thermal efficiency for gas units in 2003.
- f. Lamps Incandescent: 16.9 lumens per watt. Fluorescent 75 and 80 lumens per watt for 4-and 8-foot lamps, respectively.
- g. Electric motors Speci"es minimum efficiency End-use services modeled at the Public Law 102-486:
levels for a variety of motor equipment level. Motors EPACT92.
types and sizes. contained in new equipment must meet the standards.
- h. Federal energy management Requires Federal agencies to Superseded by Executive Order Superseded by Executive reduce energy consumption 13123, EPACT05, and EISA07. Order 13123.
20 percent by 2000 relative to 1995.
- i. Business investment energy Provides a permanent Tax credit incorporated in cash Public Law 102-486:
credit 10-percent investment tax "ow for solar generation systems. EPACT92 credit for solar property. Investment cost reduced 10 percent for solar water heaters.
C. Executive Order 13123. Greening Requires Federal agencies to Superseded by EPACT05 and Superseded by EPACT05 and the Government Through Efficient reduce energy consumption EISA07. EISA07.
Energy Management 30 percent by 2005 and 35 percent by 2010 relative to 1985 through life-cycle cost-effective energy measures.
D. Energy Policy Act of 2005 (EPACT05)
- a. Commercial package air Sets minimum efficiency Air-cooled air conditioners/heat Public Law 109-58: EPACT05.
conditioners and heat levels in 2010. pumps less than 135,000 Btu:
pumps standard of 11.2/11.0 EER and heating COP of 3.3. Air-cooled air conditioners/heat pumps greater than 135,000 Btu: standard of 11.0/10.6 EER and heating COP of 3.2.
- b. Commercial refrigerators, Sets minimum efficiency Set standard by level of Public Law 190-58: EPACT05.
freezers, and automatic levels in 2010. improvement above stock average icemakers efficiency in 2003.
- c. Lamp ballasts Bans manufacture or import Remove mercury vapor lighting Public Law 102-58: EPACT05.
of mercury vapor lamp system from technology choice ballasts in 2008. Sets menu in 2008. Set minimum minimum efficacy level for efficacy of T12 ballasts at T12 energy saver ballasts in speci"ed standard levels.
2009 and 2010 based on application.
- d. Compact "uorescent lamps Sets standard for medium Set efficacy level of compact Public Law 109-58: EPACT05.
base lamps at Energy Star "uorescent lamps at required level.
requirements in 2006.
180 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis
- e. Illuminated exit signs and Set standards at Energy Star Reduce miscellaneous electricity Number of shipments, share of traffic signals requirements in 2006. consumption by appropriate shipments that currently meet amount. standard, and estimated kWh savings per unit determine overall savings.
- f. Distribution transformers Sets standard as National Effects of the standard are Public Law 109-58: EPACT05.
Electricial Manufacturers included in estimating the share Association Class I Efficiency of miscellaneous electricity levels in 2007. consumption attributable to transformer losses.
- g. Prerinse spray valves Sets maximum "ow rate to 1.6 Reduce energy use for water Number of shipments, share of gallons per minute in 2006. heating by appropriate amount. shipments that currently meet standard, and estimated kWh savings per unit determine overall savings.
- h. Federal energy management Requires Federal agencies to The Federal share of the Public law 109-58: EPACT05.
reduce energy consumption commercial sector uses the Superseded by EISA07.
20 percent by 2015 relative to 10-year Treasury note rate as 2003 through life-cycle cost- a discount rate in equipment effective energy measures. purchase decisions as opposed to adding risk premiums to the 10-year Treasury note rate to develop discount rates for other commercial decisions
- i. Business investment tax credit Provides a 30-percent Tax credit incorporated in Public Law 109-58: EPACT05.
for fuel cells and microturbines investment tax credit for cash "ow for fuel cells and Extended through 2008 by fuel cells and a 10-percent microturbines. Public Law 109-432. Extended investment tax credit for through 2016 by EIEA08.
microturbines installed in 2006 through 2008.
- j. Business solar investment tax Provides a 30-percent Tax credit incorporated in cash Public Law 109-58: EPACT05.
credit investment tax credit for solar "ow for solar generation systems. Extended through 2008 by property installed in 2006 Investment cost reduced 30 Public Law 109-432. Extended through 2008. percent for solar water heaters. through 2016 by EIEA08.
E. Energy Independence and Security Act of 2007 (EISA07)
- a. Commercial walk-in coolers Requires use of speci"c Set standard by equivalent level of Public Law 110-140: EISA07.
and walk-in freezers energy efficiency measures in improvement above stock average equipment manufactured in or efficiency in 2003.
after 2009.
- b. Incandescent and halogen Sets maximum allowable Remove incandescent and Public Law 110-140: EISA07.
lamps wattage based on lumen halogen general service lighting output starting in 2012. systems that do not meet standard from technology choice menu in 2012.
- c. Metal halide lamp ballasts Sets minimum efficiency levels Remove metal halide lighting Public Law 110-140: EISA07.
for metal halide lamp ballasts systems that do not meet starting in 2009. standard fromtechnology choice menu in 2009. Set minimum system efficiency to include speci"ed standard levels for ballasts -ranging from 88 to 94 percent based on ballast type.
- d. Federal use of energy-efficient Requires use of energy- Increase proportion of sector Public Law 110-140: EISA07.
lighting efficient lighting "xtures and using 10 year treasury note rate bulbs in Federal buildings to for lighting purchase decisions the maximum extent possible to represent all existing and new starting in 2009. Federal "oorspace in 2009.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 181
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis
- e. Federal energy Requires Federal agencies to The Federal share of the commercial Public Law 110-140:
management reduce energy consumption per sector uses the 10-year Treasury note EISA07.
square foot 30 percent by 2015 rate as a discount rate in equipment relative to 2003 through life-cycle purchase decisions as opposed to cost-effective energy measures. adding risk premiums to the 10-year Treasury note rate to develop discount rates for other commercial decisions.
F. Energy Improvement and Extension Act of 2008 (EIEA08)
- a. Business solar Extends the EPACT05 30-percent Tax credit incorporated in cash "ow for Public Law 110-343:
investment tax credit investment tax credit for solar solar generation systems. Investment EIEA08.
property through 2016. cost reduced 30 percent for solar water heaters.
- b. Business investment tax Extends the EPACT05 30-percent Tax credit incorporated in cash "ow for Public Law 110-343:
credit for fuel cells and investment tax credit for fuel cells fuel cells and microturbines. EIEA08 microturbines and 10-percent investment tax credit for microturbines through 2016.
- c. Business investment tax Provides a 10-percent investment Tax credit incorporated in cash "ow for Public Law 110-343:
credit for CHP systems tax credit for CHP systems CHP systems. EIEA08.
installed in 2009 through 2016
- d. Business investment tax Provides a 30-percent investment Tax credit incorporated in cash "ow for Public Law 110-343:
credit for small wind tax credit for wind turbines wind turbine generation systems. EIEA08.
turbines installed in 2009 through 2016.
- e. Business investment tax Provides a 10-percent investment Investment cost for geothermal heat Public Law 110-343:
credit for geothermal tax credit for geothermal heat pump systems reduced 10 percent. EIEA08.
heat pumps pump systems installed in 2009 through 2016.
G. American Recovery and Reinvestment Act of 2009 (ARRA09)
- a. Business investment tax Removes the cap on the EIEA08 Tax credit incorporated in cash "ow for Public Law 111-5: ARRA09.
credit for small wind 30-percent investment tax credit wind turbine generation systems.
turbines for wind turbines through 2016.
- b. Stimulus funding to Provides funding for efficiency Increase the proportion of sector using Public Law 111-5: ARRA09.
Federal agencies improvement in Federal the 10-year Treasury note rate for buildings and facilities. purchase decisions to include all existing and new Federal "oorspace in years stimulus funding is available to account for new, replacement, and retro"t projects. Assume some funding is used for solar generation, small wind turbine, and fuel cell installations.
- c. State energy program Provides grants for State and local Increase the proportion of sector using Public Law 111-5: ARRA09.
funding and energy governments for energy efficiency the 10-year Treasury note rate for efficiency and and renewable energy purposes. purchase decisions to include all public conservation block State Energy Program funding buildings in years stimulus funding is grants conditioned on enactment of new available. Increase new building shell building codes. efficiency to 10 percent better than 2003 by 2018 for improved building codes. Assume some funding is used for solar generation and small wind turbine systems.
- d. Funding for smart grid Provides funding for smart grid Assume smart grid technologies cause Public Law 111-5; ARRA09.
projects demonstration projects. consumers to become more responsive to electricity price changes by increasing the price elasticity of demand for certain end uses.
182 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis Industrial sector A. Energy Policy Act of 1992 (EPACT92)
- a. Motor efficiency standards Speci"es minimum efficiency New motors must meet the Standard speci"ed in levels for a variety of motor standards. EPACT92. 10 CFR 431.
types and sizes.
- b. Boiler efficiency standards Speci"es minimum combustion All package boilers are Standard speci"ed in efficiency for package boilers assumed to meet the efficiency EPACT92. 10 CFR 431.
larger than 300,000 Btu/hr. standards. While the standards Natural Gas boilers: 80 do not apply to "eld-erected percent, oil boilers: 83 boilers, which are typically used percent. in steam-intensive industries, we assume they meet the standard in the AEO.
B. Clean Air Act Amendments (CAAA90)
- a. Process emissions Numerous process emissions Not modeled because they are CAAA90, 40 CFR 60.
requirements for speci"ed not directly related to energy industries and/or activities. projections.
- b. Emissions related to hazardous/ Numerous emissions Not modeled because they are CAAA90, 40 CFR 60.
toxic substances requirements relative to not directly related to energy hazardous and/or toxic projections.
substances.
- c. Industrial SO2 emissions Sets annual limit for industrial Industrial SO2 emissions CAAA90, Section 406 (42 SO2 emissions at 5.6 million are not projected to reach USC 7651) tons. If limit is reached, the limit (Source: EPA, speci"c regulations could be National Air Pollutant implemented. Emissions Trends:1990-1998, EPA-454/R-00-002, March 2000, p. 4-3.)
- d. Industrial boiler hazardous air Requires industrial boilers and Not explicitly modeled U.S. Environmental Protection pollutants process heaters to meet in absence of a "nal Agency, National Emissions emissions limits on HAPs to reconsideration rule. EPA Standards for Hazardous Air comply with the Maximum intends to defer enforcement Pollutants for Industrial, Achievable Control Technology until they issue a "nal Commercial, and Institutional (MACT) "oor. reconsideration rule or by late Boilers and Process Heatrates, 2012, whichever comes "rst. 40 CFR Part 63; EPA No Action Assurance Letters.
- e. Emissions from stationary diesel Requires engine New stationary engines 40 CFR Parts 60, 85, 89, 94, engines manufacturers to meet the meet the standards. 1039, 1065, and 1068.
same emission standards as nonroad diesel engines. Fully effective in 2011.
C. Energy Policy Act of 2005 (EPACT05)
- a. Physical energy intensity Voluntary commitments to Not modeled because EPACT2005, Section 106 (42 reduce physical energy participation is voluntary; USC 15811) intensity by 2.5 percent actual reductions will depend annually for 2007-2016. on future, unknown commitments.
- b. Mineral components of cement of Increase in mineral component Not modeled. EPACT2005, Section 108 (42 concrete of Federally procured cement or USC 6966).
concrete.
- c. Tax credits for coke oven Provides a tax credit of $3.00 Not modeled because no EPACT2005, Section 1321 (29 per barrel oil equuivalent, impact on U.S. coke plant USC 29).
limited to 4000 barrels per activity is anticipated.
day average. Applies to most producers of coal coke or coke gas.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 183
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis D. The Energy Independence and Security Act of 2007 (EISA2007)
- a. Motor efficiency standards Supersedes EPACT1992 Efficiency Motor purchases must meet the EISA2007 Standards no later than 2011. EPAct1992 standards through 2010; afterwards purchases must meet the EISA2007 standards.
E. The Energy Improvement and Extension Act of 2008 (EISA2008)
- a. Combined heat and power Provides an investment tax credit for Costs of systems adjusted to EIEA2008, Title I, Sec. 103 tax incentive up to 15 megawatts of capacity in re"ect the credit.
combined heat and power systems of 50 megawatts or less through 2016 Transportation sector A. Energy Policy Act of 1992 Increases the number of alternative Assumes Federal, State and Energy Policy Act of 1992, (EPACT92) fuel vehicles and alternative fuel use in fuel provided "eets meet the Public Law 102-486-Oct.
Federal, State, and fuel provided "eets. mandated sales requirements. 24, 1992.
B. Low Emission Vehicle The Clean Air Act provides California Incorporates the LEVP program Section 177 of the Clean Program (LEVP) the authority to set vehicle criteria as amended on August 4, 2005. Air Act, 42 U.S.C. sec.
emission standards that exceed Federal Assumes California, Connecticut, 7507 (1976) and CARB, standards. A part of that program Maine, Massachusetts, New California Exhaust mandates the sale of zero-emission Jersey, New York, Rhode Emissions Standards vehicles by manufacturers, other island, Vermont, Oregon, and and Test Procedures for nonattainment States are given the Washington adopt the LEVP Passenger Cars, Light-Duty option of opting into the Federal or program as amended August 4, Trucks, and Medium-Duty California emission standards. 2005 and that the proposed Vehicles, August 4, 2005.
sales requirements for hybrid, electric, and fuel cell vehicles are met.
C. Corporate Average Fuel Requires manufacturers to produce CAFE standards are increased Energy Policy Economy (CAFE) Standard for vehicles that meet a minimum Federal for model years 2011 through Conservation Act of Light Duty Vehicles average fuel economy standard, 2016 to meet the "nal CAFE 1975; Title 49 United promulgated jointly for model years rulemakings for model year 2011 States code, Chapter 329; 2012-2016 with an average greenhouse and 2012 to 2016, respectively. Energy Independence and emissions standard; cars and light trucks CAFE standards are assumed Security Act of 2007, Title are regulated separately. to increase from model year 1, Section 102; Average 2016 to 2020 to reach 35 mpg, Fuel Economy Standards as mandated by the Energy Passenger Cars and Independence and Security Act Light Trucks Model Year of 2007. 2011; Federal Register, Vol. 74, No. 59, March 2009; Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards, Final Rule, Federal Register, Vol. 75, No. 88, May 2010.
D. Electric, Hybrid, and Alternative Federal tax incentives are provided Incorporates the Federal tax IRS Technical Publication Fuel Vehicle Tax Incentives to encourage the purchase of electric, incentives for hybrid and electric 535; Business Expenses.
hybrid and or alternative fuel vehicles. vehicles.
For example, tax incentives for hybrid vehicles in the form of a $2,000 income tax deduction.
184 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis E. Plug-in Hybrid Vehicle Tax EIEA2008 grants a tax credit of $2,500 Incorporates the Federal tax Energy Improvement and Credit for PHEVs with at least 4kWh of credits for PHEVs. Extension Act of 2008, H.R.6049.
battery capacity, with larger batteries earning an additional $417 per kWh up to a maximum of $7,500 for light-duty PHEVs. The credit will apply until 250,000 eligible PHEVs are sold or until 2015, whichever comes "rst.
F. State Electric, Hybrid, and Approximately 20 States provide tax Does not incorporate State State laws in Arizona, Arkansas, Alternative Fuel Vehicle and other incentives to encourage tax and other incentives for California, Colorado, Delaware, Tax and Other Incentives the purchase of electric, hybrid and hybrid, electric, and other Florida, Georgia, Iowa, Kansas, or alternative fuel vehicles. The tax alternative fuel vehicles. Louisiana, Maine, Maryland, incentives are in the form of income Michigan, New Hampshire, New reductions, tax credits, and exemptions. York, Oklahoma, Pennsylvania, Other incentives include use of HOV Utah, Virginia, and Washington.
lanes and exemptions from emissions inspections and licensing fees. The incentives offered and the mix varies by State. For example, Georgia offers a tax credit of $5,000 for electric vehicles and Oklahoma offers a tax credit of $1,500 for hybrid and alternative fuel vehicles.
G. HD National Program; Requires on-road heavy-duty vehicle HD National program Section 202 of the Clean Air Greenhouse Gas Emissions manufacturers to produce vehicles standards begin for MY 2014 Act; Title 49 United States and Fuel Consumption that meet a minimum Federal average as set by the GHG emissions code, Chapter 32902[k]; Energy Standards for Heavy-Duty greenhouse gas emission standard, portion of the rule with the Independence and Security Act Vehicles issued by the EPA, for model years 2014- assumption that the vehicles of 2007, Title 1, Section 102; 2018. NHTSA established voluntary fuel comply with the voluntary Federal Register, Vol. 76, No. 179, consumption standards for MY 2014- portion of the rule for fuel September 2011.
2015, and mandatory fuel consumption consumption. The model standards for MY 2016 and beyond for on-allows for both the engine road heavy-duty trucks and their engines; and chassis technologies to vocational and combination engines are meet the standards.
regulated separately.
Electric power generation A. Clean Air Act Amendments Established a national limit on electricity Sulfur dioxide cap and trade Clean Air Act Amendments of 1990 (CAAA90) generator emissions of sulfur dioxide to program is explicitly of 1990, Title IV, Sections 401 be achieved through a cap-and-trade modeled, choosing the through 406, Sulfur Dioxide program. optimal mix of options Reduction Program, 42 U.S.C.
for meeting the national 7651a through 7651e.
emissions cap.
Set boiler-type-speci"c nitrogen oxide Assumes each boiler installs Clean Air Act Amendments emissions limits for electricity generators. the options necessary to of 1990, Title IV, Sections comply with their nitrogen 407, Nitrogen Oxide Emission oxide emissions limit. Reduction Program, 42 U.S.C.
7651f.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 185
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis Requires the EPA to establish national These standards are not Clean Air Act Amendment of ambient air quality standards explicitly represented, but the 1990, Title I, Sections 108 and (NAAQS). In 1997, EPA set new Cross-State Air Pollution Rule is 109, National Ambient Air Quality standards for ground level ozone and incorporated (described below) Standards for Ozone, 40 CFR "ne particulates. EPA is currently and was developed to help Part 50, Federal Register, Vol 68, determining which areas of the ountry States meet their NAAQS. No 3, January 8, 2003. National are not in compliance with the new Ambient Air Quality Standards standards. Area designations were for Particulate Matter, 40 CFR Part made in December 2004. States 50, Federal Register, Vol. 62, No.
submitted their compliance plans, and 138, July 18, 1997.
have until 2009-2014 to bring all areas into compliance.
B. Cross-State Air Pollution CSAPR requires States to reduce SO2 Cap and trade programs for SO2 Environmental Protection Agency, Rule (CSAPR) and NOx emissions from power plants. and NOx are modeled explicitly, Cross-State Air Pollution Rule, CSAPR consists of four individual cap allowing the model to choose website epa.gov/airtransport.
and trade programs, covering two the best method for meeting the different SO2 groups, an annual NOx emission caps. Although actual group and a seasonal NOx group. A implementation of the rule has total of 23 States are subject to annual been delayed because of a stay, limits, and 25 States are subject to the ruling was not made in time seasonal limits. to remove the rule from the AEO2012.
C. Mercury and Air Toxics MATS sets standards to reduce air The EMM assumes that all Environmental Protection Standards (MATS) pollution from coal and oil-"red power coal-"red generating plants Agency, Mercury and Air Toxics plants greater than 25 megawatts. above 25 megawatts will comply Standards, website epa.gov/mats.
The rule requires plants achieve beginning in 2015. Plants are the maximum achievable control assumed to reduce mercury technology for mercury, hydrogen emissions by 90 percent relative chloride (HCl) and "ne particulate to uncontrolled levels. Because matter (PM 2.5). the EMM does not model HCl or PM 2.5 explicitly, to meet those requirements, coal plants are required to install either an FGD or a dry sorbent injection system including a full fabric "lter.
D. Energy Policy Act of 1992 Created a class of generators referred Represents the development Energy Policy Act of 1992, Title (EPACT92) to as exempt wholesale generators of Exempt Wholesale VII, Electricity, Subtitle A, Exempt (EWGs), exempt from PUHCA as long Generators (EWGs) or what Wholesale Generators.
as they sell wholesale power. are now referred to as independent power producers (IPPs) in all regions.
E. The Public Utility Holding PUHCA is a Federal statue which was It is assumed that holding Public Utility Holding Company Company Act of 1935 enacted to legislate against abusive companies act competitively Act of 1936.
(PUHCA) practices in the utility industry. The and do not use their regulated act grants power to the U.S. Securities power businesses to cross-and Exchange Commission (SEC) subsidize their unregulated to oversee and outlaw large holding businesses.
companies which might otherwise control the provision of electrical service to large regions of the country.
It gives the SEC power to approve or deny mergers and acquisitions and, if necessary, force utility companies to dispose of assets or change business practices if the companys structure of activities are not deemed to be in the public interest.
186 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis F. FERC Orders 888 and 889 FERC has issued two related rules: These orders are represented in Promoting Wholesale Competition Orders 888 and 889, designed to the forecast by assuming that all Through Open Access, Non-bring low-cost power to consumers generators in a given region are Discriminatory Transmission through competition, ensure able to satisfy load requirements Services by Public Utilities; Public continued reliability in the industry, anywhere within the region. Utilities and Transmitting Utilities, and provide for open and equitable Similarly, it is assumed that ORDER NO. 888 (Issued April transmission services by owners of transactions between regions 24, 1996), 18 CFR Parts 35 and these facilities. Speci"cally, Order will occur if the cost differentials 385, Docket Nos. RM95-8-000 888 requires open access to the between them make it economic and RM94-7-001. Open Access transmission grid currently owned and to do so. Same-Time Information System operated by utilities. The transmission (formerly Real-Time Information owners must "le nondiscriminatory Networks) and Standards of tariffs that offer other suppliers the Conduct, ORDER NO. 889, same services that the owners provide (Issued April 24, 1996), 18 CFR for themselves. Order 888 also allows Part 37, Docket No. RM95-9-000.
these utilities to recover stranded costs (investments in generating assets that are unrecoverable due to consumers selecting another supplier). Order 889 requires utilities to implement standards of conduct and a Open Access Same-time Information System (OASIS) through which utilities and non-utilities can receive information regarding the transmission system.
Consequently, utilities are expected to functionally or physically unbundle their marketing functions from their transmission functions.
G. New Source Review (NSR) On August 28, 2003, the EPA issued It is assumed that coal plants will EPA, 40 CFR Parts 51 and a "nal rule de"ning certain power be able to increase their output 52, Deterioration (PSD) and plant and industrial facility activities as electricity demand increases. Non-Replacement Provision as routine maintenance, repair and Their maximum capacity factor of the Vol. 68, No. 207, page replacement, which are not subject to is set at 75 percent. No increases 61248, Prevention of Signi"cant new source review (NSR). As stated in the capacity of existing plants Attainment New Source Review by EPA, these changes provide a is assumed. If further analysis (NSR): Equipment Routine category of equipment replacement shows that capacity uprates may Maintenance, Repair and activities that are not subject to Major result from the NSR rule, they Replacement Exclusion; Final NSR requirements under the routine will be incorporated in future Rule, Federal Register, October 27, maintenance, repair and replacement AEOs. However, at this time, 2003.
(RMRR) exclusion.[1] Essentially this the NSR rule is being contested means that power plants and industrial in the courts.
facilities engaging in RMRR activities will not have to get preconstruction approval from the State or EPA and will not have to install best available emissions control technologies that might be required if NSR were triggered.
H. State RPS Laws, Mandates, Several States have enacted laws The AEO reference case The 30 States with RPS or other and Goals requiring that a certain percentage represents the Renewable mandates providing quanti"ed of their generation come from Portfolio Standard (RPS) or projections are detailed in the qualifying renewable sources. substantively similar laws from Legislation and Regulations 30 States and the District of section of this report.
Columbia. As described in the U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 187
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis Renewable Fuels Module chapter of this document, mandatory targets from the various States are aggregated at the regional level, and achievement of nondiscretionary compliance criteria is evaluated for each region.
I. Regional and State Air The Northeast Regional Greenhouse The impact of RGGI is Regional Greenhouse Gas Initiative Emissions Regulations Gas Initiative (RGGI) applies to included in the EMM, making Model rule, www.rggi.org fossil-fueled power plants over 25 adjustments when needed to megawatts in the Northeastern estimate the emissions caps United States. The State of NJ at the regional level used in withdrew in 2011, leaving 9 States NEMS.
in the program. The rule caps CO2 emissions and requires they account for CO2 emitted with allowances purchased at auction.
The California Assembly Bill 32 The EMM models the cap- California Code of Regulations, (AB32) sets GHG reduction goals for and-trade program explicitly Subchapter 10 Climate Change, 2020 for California. A cap-and-trade for CO2 for California. Because Article 5, Sections 95800 to program was designed to enforce the the other modules of NEMS 96023, Title 17, California Cap caps. The cap-and-trade program cannot represent State-speci"c on Greenhouse Gas Emissions applies to multiple economic sectors legislation, the impacts are not and Market-Based Compliance including electric power plants, included for other sectors. The Mechanisms, (Sacramento, CA:
large industrial facilities, suppliers EMM set the electric power July 2011).
of transportation fuel and suppliers cap based on the power of natural gas. Emissions resulting sectors share of total emissions from electricity generated outside in 2008 (25 percent).
California but consumed in the State are also subject to the cap.
J. Energy Policy Act of 2005 Extended and substantially EPACT2005 also adds a PTC Energy Policy Act of 2005, expanded and modi"ed the for up to 6,000 megawatts of Sections 1301, 1306, and 1307 Production Tax Credit, originally new nuclear capacity and a created by EPACT1992. $1.3 billion investment tax credit for new or repowered coal-"red power projects. The tax credits for renewables, nuclear and coal projects are explicitly modeled as speci"ed in the law and subsequent amendments.
K. American Recovery and Extends the Production Tax Credit The extensions of the PTC American Recovery and Reinvestment Act of 2009 (PTC) to wind facilities constructed and 30-percent ITC are Reinvestment Act of 2009, by December 31, 2012 and to other represented in the AEO Division B, Title I, Sec. 1101, 1102, eligible renewable facilities reference case as speci"ed and 1603.
constructed by December 31, 2013. in the law. The AEO does not Allows PTC-eligible facilities to distinguish between the claim a 30-percent investment tax effects of the 30-percent ITC credit (ITC) instead of the PTC. and the equivalent cash grant, Projects starting construction by and the cash grant is not the end of 2010 (subsequently speci"cally modeled.
extended to the end of 2011) may elect to take a cash grant equal to the value of the 30-percent ITC instead of either tax credit.
188 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis ARRA provided $6 billion to pay AEO2012 includes projects that American Recovery and the cost of guarantees for loans have received loan guarantees Reinvestment Act of 2009, authorized by the Energy Policy under this authority, but does Title IV, Energy and Water Act of 2005. The purpose of these not assume automatic award of Development, Section 406.
loan guarantees is to stimulate the the loans to potentially eligible deployment of conventional renewable technologies.
and transmission technologies and innovative biofuels technologies.
However, to qualify, eligible projects must be under construction by September 30, 2011.
ARRA provides $4.5 billion for smart In the electricity module, it was American Recovery and grid demonstration projects. These assumed that line losses would Reinvestment Act of 2009, generally include a wide array of fall slightly, peak loads would Title IV, Energy and Water measurement, communications, and fall as customers shifted their Development, Section 405.
control equipment employed through- usage patterns, and customers out the transmission and distribution would be more responsive to system that will enable real-time pricing signals.
monitoring of the production, "ow, and use of power from generator to consumer.
ARRA provides $800 million to fund It was assumed that one gigawatt American Recovery and projects under the Clean Coal Power of new coal with sequestration Reinvestment Act of 2009, Initiative program focusing on capture capacity would come online by Title IV, Energy and Water and sequestration of greenhouse gases. 2017. Development Oil and gas supply A. The Outer Continental Shelf Mandates that all tracts offered by Incorporates royalty rates based 43 U.S.C. SS 1331-1356 (2002).
Deep Water Royalty Relief November 22, 2000, in deep water in on water depth.
Act (DWRRA) certain areas of the Gulf of Mexico must be offered under the new bidding system permitted by the DWRRA.
The Secretary of the Interior must offer such tracts with a speci"c minimum royalty suspension volume based on water depth.
B. Energy Policy and Required the USGS to inventory oil and To date, the Rocky Mountain oil Scienti"c Inventory of Onshore Conservation Act gas resources beneath Federal lands. and gas resource inventory has Federal Lands: Oil and Gas Amendments of 2000 been completed by the USGS. Resources and Reserves and The results of this inventory the Extent and Nature of have been incorporated in the Restrictions or Impediments technically recoverable oil and to their Development: The gas resource volumes used for the Paradox/San Juan, Uinta/
Rocky Mountain region. Piceance, Greater Green River, and Powder River Basins and the Montana Thrust Belt. Prepared by the Departments of Interior, Agriculture and Energy, January 2003.
C. Section 29 Tax Credit for The Alternative Fuel Production Credit The Section 29 Tax Credit Alternative Fuel Production Nonconventional Fuels (Section 29 of the IRC) applies to expired on December 31, 2002, Credit (Section 29 of the quali"ed nonconventional fuels from and it is not considered in new Internal Revenue Code), initially wells drilled or facilities placed in production decisions. However, established in the Windfall Pro"t service between January 1, 1980, and the effect of these credits Tax of 1980.
December 31, 1992. Gas production is implicitly included in the from qualifying wells could receive a $3 parameters that are derived from historical data re"ecting such credits.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 189
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis (1979 constant dollars) per barrel of oil equivalent credit on volumes produced through December 31, 2002. The quali"ed fuels are: oil produced from shale and tar sands; gas from geopressurized brine, Devonian shale, coal seams, tight formations, and biomass; liquid, gaseous, or solid synthetic fuels produced from coal; fuel from quali"ed processed formations or biomass; and steam from agricultural products.
D. Energy Policy Act of 2005 Established a program to provide Additional oil resources were Title III, Section 354 of the grants to enhance oil and gas added to account for increased Energy Policy Act of 2005.
recovery through CO2 injection. use of CO2-enhanced oil recovery.
Natural gas transmission and distribution A. Alaska Natural Gas Disallows approval for a pipeline to Assumes the pipeline P.L. 108-324.
Pipeline Act, Sections enter Canada via Alaska north of 68 construction cost estimate for the 101-116 of the Military degrees latitude. Also, provides southernAlaska pipeline route Construction Hurricane Federal guarantees for loans and other in projecting when an Alaska Supplemental debt obligations assigned to infrastruc- gas pipeline would be pro"table Appropriations Act, 2005. ture in the United States or Canada to build. With recent increased related to any natural gas pipeline in cost estimates, well beyond system that carries Alaska natural gas $18 billion, the loan guarantee to the border between Alaska and is assumed to have a minimal Canada south of 68 degrees north impact on the build decision.
latitude. This authority would expire 2 years after the "nal certi"cate of public convenience and necessity is issued. The guarantee will not exceed 1) 80 percent of the total capital costs (including interest during construction), 2) $18 billion (indexed for in"ation at the time of enactment), or 3) a term of 30 years.
B. American Jobs Creation Provides a 7-year cost-of-investment The change in the recovery P.L. 108-357.
Act of 2004, Sections recovery period for the Alaska natural period is assumed to have a 706 and 707. gas pipeline, as opposed to the currently minimal impact on the decision allowed 15-year recovery period, for to build the pipeline. The tax purposes. The provision would be assumed treatment costs are effective for property placed in service based on company estimates after 2013, or treated as such. Effectively made after these tax provisions extends the 15-percent tax credit were enacted.
currently applied to costs related to enhanced oil recovery to construction costs for a gas treatment plant on the North Slope that would feed gas into an Alaska pipeline to Canada.
190 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis C. Pipeline Safety Imposes a stricter regime on pipeline Costs associated with P.L. 107-355, 116 Stat. 2985.
Improvement Act of 2002 operators designed to prevent leaks and implementing the new safety ruptures. features are assumed to be a small percentage of total pipeline costs and are partially offset by bene"ts gained through reducing pipeline leakage. It is assumed that the Act accelerates the schedule of repair work that would have been done otherwise.
D. FERC Order 436 (Issued Order 436 changed gas transmission from Natural gas is priced at the 50 F. R. 42408, FERC Statutes in 1985) a merchant business, wherein the pipeline wellhead at a competitive rate and Regulations Paragraph buys the gas commodity at the inlet and determined by the market. The 30,665 (1985).
sells the gas commodity at the delivery "ow of gas in the system is a point, to being a transportation business function of the relative costs and wherein the pipeline does not take title to is set to balance supply, demand, the gas . Order 436 permitted pipelines and prices in the market.
to apply for blanket transportation Transportation costs are based certi"cates, in return for becoming on a regulated rate calculation.
nondiscriminatory, open-access transporters. Order 436 also allocated gas pipeline capacity on a "rst-come, "rst-serve basis, allowed pipelines to discount below the maximum rate, allowed local gas distributors to convert to transportation only contracts, and created optional expedited certi"cates for the construction of new facilities.
E. FERC Order 636 (Issued FERC Order 636 completed the separa- A straight-"xed-variable rate 57 F.R. 13267, FERC Statutes in 1992) tion of pipeline merchant services from design is used to establish and Regulations Paragraph pipeline transportation services, requiring regulated rates. To re"ect some 30,939 (1992) pipelines to offer separate tariffs for "rm of the "exibility built into the transportation, interruptible transporta- system, the actual tariffs charged tion, and storage services. Order 636 are allowed to vary from the also permitted pipelines to resell regulated rates as a function of unused "rm capacity as interruptible the utilization of the pipeline.
transportation, gave shippers the right to End-use prices are set separately "rst refusal at the expiration of their "rm for "rm and interruptible transportation contracts, adopted customers for the industrial and Straight-Fixed-Variable rate methodo- electric generation sectors.
logy, and created a mechanism for pipelines to recover the costs incurred by prior take-or-pay contracts.
F. Hackberry Decision Terminated open access requirements This is re"ected in the structural Docket No. PL02-9, Natural Gas for new onshore LNG terminals and representation of U.S. LNG imports Markets Conference (2002).
authorized them to charge market-based in EIAs International Natural rather than cost-of-service Gas Model, used to develop U.S.
rates. LNG import supply curves for the NGTDM.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 191
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis G. Maritime Security Act of Transfers jurisdiction over offshore This is re"ected in the structural P.L. 107-295.
2002 Amendments to the LNG facilities from FERC to the representation of U.S. LNG imports Deepwater Port Act of 1974 Maritime Administration (MARAD) in EIAs International Natural and the Coast Guard, both under the Gas Model, used to develop U.S.
Department of Transportation (DOT), LNG import supply curves for the provides these facilities with a new, NGTDM.
streamlined application process, and relaxes regulatory requirements (offshore LNG facilities are no longer required to operate as common carriers or to provide open access as they did while under FERC jurisdiction).
H. Energy Policy Act of 2005 Allowed natural gas storage Storage rates are allowed to vary Title III, Section 312 of the Energy facilities to charge market-based from regulation-based rates Policy Act of 2005.
rates if it was believed they would not depending on market conditions.
exert market power.
I. Federal Motor Fuels Excise Taxes are levied on each gallon or Federal motor fuels excise taxes 26 USC 4041.
Taxes for Compressed gasoline-gallon equivalent of natural on natural gas fuel for vehicles Natural Gas and Lique"ed gas. are included in retail prices and Natural Gas in Vehicles are assumed to be extended inde"nitely at current nominal rates.
J. State Motor Fuels Taxes for Taxes are levied on each gallon, State motor fuels excise taxes Determined by review of existing Compressed Natural Gas gasoline-gallon equivalent, or diesel- on natural gas fuel for vehicles State laws.
and Lique"ed Natural Gas gallon equivalent of natural gas. are included in retail prices and in Vehicles are assumed to be extended inde"nitely at current nominal rates.
" 6
A. Ultra-Low-Sulfur Diesel 80 percent of highway diesel pool must Re"ected in diesel speci"cations. 40 CFR Parts 69, 80, 86, 89, 94, (ULSD) regulations under contain 15 ppm sulfur or less starting 1039, 1048, 1065, and 1068.
the Clean Air Act in fall 2006. By mid-2010, all highway Amendment of 1990 diesel must be 15 ppm or less. All nonroad, locomotive, and marine diesel fuel produced must contain less than 500 ppm starting mid-2007. By mid-2010 nonroad diesel must contain less than 15 ppm. Locomotive and marine diesel must contain less than 15 ppm by mid-2012.
B. Mobile Source Air Toxics Establishes a list of 21 substances Modeled by updating gasoline 40 CFR Parts 60 and 86.
(MSAT) Controls Under the emitted from motor vehicles and speci"cations to most current Clean Air Act Amendment known to cause serious human EPA gasoline survey data (2005) of 1990 health effects, particularly benzene, representing anti-backsliding formaldehyde, 1.3 butadiene, requirements.
acetaldehyde, diesel exhaust organic gases, and diesel particulate matter.
Establishes anti-backsliding and anti-dumping rules for gasoline.
192 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis C. Low-Sulfur Gasoline Gasoline must contain an average Re"ected in gasoline speci"cations. 40 CFR Parts 80, 85 and 86.
Regulations Under the Clean of 30 ppm sulfur or less by 2006.
Air Act Amendment of 1990 Small re"ners may be permitted to delay compliance until 2008.
D. MTBE Bans in 25 States 23 States ban the use of MTBE in Ethanol assumed to be the oxyge- State laws in Arizona, gasoline by 2007. nate of choice in RFG where MTBE California, Colorado, is banned Connecticut, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Ohio, Rhode Island, South Dakota, Vermont, Washington, and Wisconsin.
E. Regional Clean Fuel States with air quality problems can Re"ected in PADD-level gasoline State implementation plans Formulations specify alternative gasoline or diesel and diesel speci"cations. required by the Clean Air Act formulations with EPAs permission. Amendments of 1990, as California has long had authority to approved by EPA.
set its own fuel standards.
F. Federal Motor Fuels Excise Taxes are levied on each gallon Gasoline, diesel, and ethanol blend 26 USC 4041 Extended by Taxes of transportation fuels to fund tax rates are included in end-use American Jobs Creation Act infrastructure and general revenue. prices and are assumed to be of 2004 These taxes are set to expire at extended inde"nitely at current various times in the future but are nominal rates.
expected to be renewed, as they have been in the past.
G. State Motor Fuel Taxes Taxes are levied on each gallon of Gasoline and diesel rates are Determined by review of transportation fuels. The assumption included in end-use prices and are existing State laws performed that State taxes will increase at the assumed to be extended inde"nitely semi-annually by EIAs Office rate of in"ation supports an implied in real terms (to keep pace with of Energy Statistics.
need for additional highway revenues in"ation).
as driving increases.
H. Diesel Excise Taxes Phases out the 4.3 cents excise tax Modeled by phasing out. American Jobs Creation Act on railroads between 2005 and 2007. of 2004, Section 241.
I. Energy Policy Act of 2005 (EPACT05)
- a. Ethanol/biodiesel tax Petroleum product blenders The tax credits are applied against 26 USC 40, 4041 and credit may claim tax credits for blending the production costs of the products American Jobs Creation ethanol into gasoline and for into which they are blended. Ethanol Act of 2004. Biodiesel tax blending biodiesel into diesel fuel is used in gasoline and E85. Virgin credits extended to 2008 or heating oil. The credits may be biodiesel is assumed to be blended under Energy Policy Act of claimed against the Federal motor into highway diesel, and nonvirgin 2005.
fuels excise tax or the income tax. biodiesel is assumed to be blended The tax credits are 51 per gallon into nonroad diesel or heating oil.
of nonvirgin biodiesel, and $1.00 per gallon of virgin biodiesel. The ethanol tax credit expires in 2010.
The biodiesel tax credits expire after 2008.
- b. Renewable Fuels Standard This section has largely been Energy Policy Act of 2005, (RFS) rede"ned by EISA07 (see below); Section 1501.
however, EPA rulemaking completed for this law was assumed to contain guiding principles of the rules and administration of EISA07.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 193
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis
- c. Elimination of oxygen Within 270 days of enactment Oxygenate waiver already an Energy Policy Act of 2005, content requirement in of the Act, except for California option of the model. MTBE is Section 1504.
reformulated gasoline where it is effective assumed to phase out in 2006 immediately. resulting from the petroleum industrys decision to discon-tinue use. AEO projection may still show use of ethanol in gasoline based on the economics between ethanol and other gasoline blending components.
- d. Coal gasi"cation provisions Investment tax credit program Two CTL units are available to Energy Policy Act of 2005, for qualifying advanced clean build with lower capital costs Section 1307.
coal projects including Coal-to- re"ecting the provisions funding.
Liquids Projects.
J. Energy Independence and Security Act of 2007 (EISA07)
- a. Renewable Fuels Standard Requires the use of 36 billion The RFS is included in AEO2012, (RFS) gallons of ethanol per year however it is assumed that the by 2022, with corn ethanol schedule for cellulosic biofuel is limited to 15 billion gallons. adjusted downward consistent Any other biofuel may be used with waiver provisions contained to ful"ll the balance of the in the law.
mandate, but the balance must include 16 billion gallons per year of cellulosic biofuel by 2022 and 1 billion gallons per year of biodiesel by 2012.
K. State Heating Oil Mandates A number of Northeastern All State regulations included as Connecticut State Senate States passed legislation that legislated in AEO2012. 2010 EIA Bill 382, Maine State Legislature reduces the maximum sulfur Heating Oil consumption data HP1160, NJ State Department content of heating oil to used to calculate respective of Environmental Protection, between 15 and 50 ppm in State/Census Division shares Amendment N.J.A.C.
different phases through 2016. for new consumption of low 7:27-9.2, New York State sulfur diesel as heating oil. Senate Bill S1145C.
L. California Low Carbon Fuel California passed legislation The LCFS is included in AEO2012 California Air Resources Standard (LCFS) which is designed to reduce the as legislated for gasoline and Board, Final Regulation Order:
Carbon Intensity (CI) of motor diesel fuel sold in California, and Subarticle 7. Low Carbon Fuel gasoline and diesel fuels sold for other regulated fuels. The Standard.
in California by 10 percent Paci"c Census Division 9 was between 2012 and 2020 used as a proxy.
through the increased sale of alternative low-carbon fuels.
M. EPA ETS Waiver EPA approved two waivers for These two waivers were EPA-HQ-OAR-2009-0211; the use of ethanol motor included and modeled in FRL-9215-5, EPA-HQ-OAR-gasoline blends of up to 15 AEO2012 based on forecasted 2009-0211; FRL-9258-6.
percent in vehicles 2001 and vehicle "eets and potential newer. infrastructure and liability setbacks.
Coal supply A. July 21, 2011 Memorandum: On July 21, 2011, the EPA The impact of the EPAs Permit program for discharges Improving EPA Review of issued a set of "nal guide- guidelines for surface coal of dredged or "ll material, which Appalachian Surface Coal Mining lines to several of its regional mining operations in Appalachia is administered primarily by the Operations Under the Clean Water offices for monitoring the is represented by downward U.S. Army Corps of Engineers Act, National Environmental Policy compliance of surface adjustments to the coal mining pursuant to Section 404 of Act, and the Environmental Justice coal mining operations in productivity assumptions for the CWA, 33 U.S.C. 1344; the Executive Order Appalachia. The guidelines Central Appalachian surface National Pollutant Discharge relate primarily to the ongoing mines toward the productivity Elimination System (NPDES),
controversy over levels for smaller surface mines which is administered by the in the region. EPA and authorized States 194 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Legislation Brief description AEO handling Basis use of the mountaintop removal pursuant to Section 402 of method at a number of surface the CWA, 33 U.S.C. 1342; the coal mining operations in National Environmental Policy Central Appalachia primarily in Act; and the Environmental southern West Virginia and Justice Executive Order (E.O.
eastern Kentucky. While the 12898) guidelines require a more rigorous review for all new surface coal mines in Appalachia, EPA indicates that the practice of valley "lls, primarily associated with the mountaintop removal method, is the aspect of Appalachian coal mining that will be most scrutinized.
Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 195
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Abbreviations:
AB: Assembly Bill AB32: California Assembly Bill 32 ACI: Activated carbon injection AEO: Annual Energy Outlook AEO2012: Annual Energy Outlook 2012 AFUE: Average Fuel Use Efficiency ANWR: Artic National Wildlife Refuge ARRA2009: American Recovery and Reinvestment Act of 2009 ASHRAE: American Society of Heating Refrigerating, and Air-Conditioning Engineers Blue Chip: Blue Chip Consensus BTL: Biomass-to-liquids Btu: British Thermal Unit CAFE: Corporate Average Fuel Economy CAIR: Clean Air Interstate Rule CARB: California Air Resources Board CBECS: Commercial Building Energy Consumption Survey CBO: Congressional Budget Office CBTL: Coal- and biomass-to-liquids CCS: Carbon capture and storage CFR: Code of Federal Regulations CHP: Combined heat and power CI: Carbon intensity CMM: Coal Market Module CNG: Compressed natural gas CO2: Carbon dioxide CO2-EOR: Carbon dioxide-enhanced oil recovery CSAPR: Cross-State Air Pollution Rule CTL: Coal-to-liquids DG: Distributed generation DGE: Diesel gallon equivalent DOE: U.S. Department of Energy DOT: Department of Transportation DSI: Direct sorbent injection DWRRA: Deep Water Royalty Relief Act E10: Motor gasoline blend containing up to 10 percent ethanol E15: Motor gasoline blend containing up to 15 percent ethanol E85: Motor fuel containing up to 85 percent ethanol EERE: Energy Efficiency and Renewable Energy EER: Energy Efficient Ratio EIA: U.S. Energy Information Administration EIEA2008: Energy Improvement and Extension Act of 2008 EISA2007: Energy Independence and Security Act of 2007 EOR: Enhanced oil recovery EPA: U.S. Environmental Protection Agency EPACT92: Energy Polic y Act of 1992 EPACT05: Energy Policy Act of 2005 EUR: Estimated ultimate recovery EV: Electric vehicle EVA: Energy Ventures Analysis EWGs: Exempt Wholesale Generators FFV: Flex-fuel vehicle FEMP: Federal Energy Management Program FERC: Federal Energy Regulatory Commission FGD: Flue gas desulfurization HDV: Heavy-duty Vehicles HERS: Home Energy System Rating HVAC: Heating, Ventilation, and Air Conditioning GDP: Gross domestic procduct GHG: Greenhouse Gases 196 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Abbreviations:
GTL: Gas-to-liquids GVWR: Gross vehicle weight rating HAP: Hazardous air pollutant HB: House Bill HCI: Hydrogen chloride HD: Heavy-duty HDV: Heavy-duty vehicle HERS: Home Energy System Rating HEV: Hybrid electric vehicle Hg: Mercury HVAC: Heating Ventilation, and Air Conditioning ICE: Internal combustion engine IDM: Industrial Demand Module IEA: International Energy Agency IECC2006: 2006 International Energy Conversion Code IEM: International Energy Module IHSGI: IHS Global Insight INFORUM: Interindustry Forecasting Project at the University of Maryland IOU: Investor-owned utility IREC: Interstate Renewable Energy Council ITC: Investment Tax Credit kWh: Kilowatthour LBNL: Lawrence Berkeley National Laboratory LCFS: Low Carbon Fuel Standard LDV: Light-duty vehicle LED: Light-emitting diode LFMM: Liquid Fuels Market Module LNG: Lique"ed natural gas MARAD: Maritime Administration MATS: Mercury and Air Toxics Standards MAM: Macroeconomic Activity Module MCF: Thousand Cubic Feet MEF: Modi"ed Energy Factor mmt: Million metric tons MMTCO2e: Million metric tons carbon dioxide equivalent mpg: Miles per gallon MSAT: Mobile Source Air Toxics MSRP: Manufacturers suggested retail price MTBE: Methyl Tertiary-Butyl Ether MY: Model year NAICS: North American Industry Classi"cation System NEMS: National Energy Modeling System NERC: North American Electric Reliability Corportion NGL: Natural gas liquids NGPL: Natural gas plant liquids NGTDM: Natural Gas Transmission and Distribution Module NGV: Natural gas vehicle NHTSA: National Highway Traffic Safety Administration NOx: Nitrogen oxides NRC: U.S. Nuclear Regulatory Commission OASIS: Open Access Same-Time Information System OECD: Organization for Economic Cooperation and Development OMB: Office of Management and Budget OPEC: Organization of the Petroleum Exporting Countries P&G: Purvin & Gertz PADD: Petroleum Administration for Defense District PCs: Personal computers PHEV: Plug-in Hybrid Electric Vehicles U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012 197
Appendix A: Handling of Federal and selected State legislation and regulation in the AEO Abbreviations:
P.L.: Public Law PM: Particulate matter PM25: Particulate matter less than 2.5 microns diameter PMM: Petroleum Market Module PPM: Parts Per Million PTC: Production tax credit PUHCA: Public Utility Holding Company Act of 1935 PV: Solar photovoltaic RAC: U.S. Re"ner Acquisition Cost RECS: Residential Enegy Consumption Survey RFM: Renewable Fuels Module RFS: Renewable fuel standard RGGI: Regional Greenhouse Gas Initiative RPS: Renewable portfolio standard SB: Senate Bill SCR: Selective catalytic reduction SEER: Strategic Energy and Economic Research, Inc.
SEIA: Solar Energy Industries Association SNCR: Selective noncatalytic reduction SO2: Sulfur dioxide STEO: Short-Term Energy Outlook TAPS: Trans-Alaska Pipeline System TRR: Technically recoverable resource UEC: Unit energy consumption USLD: Ultra-Low-Sulfur Diesel U.S.C.: United States Code UPS: Uninterruptible power supply USGS: United States Geologicals Survey VIUS: Vehicle Inventory and Use Survey VMT: Vehicle miles traveled WTI: West Texas Intermediate ZEV: Zero Emission Vehicle 198 U.S. Energy Information Administration l Assumptions to the Annual Energy Outlook 2012