ML19351C942
| ML19351C942 | |
| Person / Time | |
|---|---|
| Site: | 05000471 |
| Issue date: | 05/01/1980 |
| From: | Desmond J, Lydon J BOSTON EDISON CO. |
| To: | |
| Shared Package | |
| ML19351C943 | List: |
| References | |
| NUDOCS 8010080406 | |
| Download: ML19351C942 (170) | |
Text
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Applicants' Exhibit 21-A O Tha Ccmmsnwealth of MassachusottsM
- - Energy Facilities Siting Council /0 4 1 (
- o W,e ci '8 y BOSTON EDISON COMPANY E %,j 9 /
LONG-RANGE FORECAST h OF l ELECTRIC POWER NEEDS AND REQUIREMENTS
- l. Annual Supplement 1 D i'
i' 1980 1989 l, Volume i Il N e l- , inna. l j y i flI a t
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i 'w , MAY 1,1980 il 8010080406 l it.
_- y i e eo ,a l BOSTON EDISON COMPANY sea soVLSToM STREET Boston. MASSAcMUSETTE O2199 JAuse M. LYonN
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May 1, 1980 I Commonwealth of Massachusetts Energy Facilities Siting Council 73 Tremont Street, Room 300 Boston, b asachusetts 02108 Re: Boston Edison Company i Supplement to Long Range Forecast l 1980 - 1989 Gentlemen: In accordance with the provisions of General Laws, Chapter 164, Section 69I and the Regulations of the Energy Facilities Siting Council. I file h'erewith Boston Edison Company's " Annual Supplement 1-D, 1980 - 1989, Volume I". This supplement updates and revises the "Long Range Forecast of Electric Power Needs and Requirements, 1976 - 1985" filed on April 30, i 1976. I respectfully request that this Supplement be approved by the Council. Very truly you s,
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- i. ~ LONG-RANGE FORECAST OF l ELECTRIC POWER NEEDS AND REQUIRDfENTS Annual Supplement 1-D j :
{ 1980 -1989 i , Volume r I Pursuant to General Laws Chapter 164, Section 691 i l Br BOSTON EDISON COMPANY 1 800 Boylston Street l Boston, Massachusetts 02199 i l Name of the Officer to whom Mr. James M. Lydon communications should be directed Senior Vice President with respect to this volume: Boston Edison Company 800 Boylston Street Boston, Massachusetts 02199 Legal Counsel: John J. Desmond, III, Esq. William S. Stowe, Esq. Boston Edison Company 800 Boylston Street i Boston, Massachusetts 02199 1, l
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-_ o LONG RANGE FORECAST OF ELECTRIC POWER NEEDS AND REQUIREMENTS ANNUAL SUPPLIMENT 1-D 1980 - 1989 TABLE OF CONTENTS f
Volume I Section I Introduction And Summary Section II Electric Power Needs And Requirements Volume II Section I Existing And Planned Generation Facilities Section II Existing and Proposed Transmission And t Sabstation Facilities Section III Agreements For Electric Service e emme l l l f 4 .e o me e-auum e e.e ees- e -e .o* maamm e-o 4 me
e e< y SECTION I INTRODUCTION AND
SUMMARY
INTRODUCTION
~
This report is the fourth annual supplement to the "Long Range Forecast of Electric Power Needs and Requirements" submitted by the Boston Edison Company to the Energy Facilities Siting Council of the Comunonwealth of Massachusetts, April 30, 1976. This supplement modifies the forecast of future electric energy needs and peak demands and the Company's previous plans to meet these needs by incorporating the latest available pertinent information.
SUMMARY
i
; Section II of Volume I of this supplement presents a revised energy and demand forecast for Boston Edison Company as well as the methodology used in arriving at the new forecasts. Section I of Volume II of this supplement presents the ! latest data regarding the Company's generating facilities. Section II of Volume II updates the status of the Company's existing transmission facilities and revises the forecast concerning future facilities where appropriate.
Section III of Volume II presents information concerning agreements with other electric companies for the purchase and sale of electric energy. 1 I w 4
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F l 4 l TABLE OF CONTENTS i j s M i . INTRODUCTION AND
SUMMARY
l-29A l; DEMOGRAPHICS 30-44 RESIDENTIAL CLASS 45-64 i COMMERCIAL CLASS 65-87 I i INDUSTRIAL CLASS 88-127 3 1 1 128-130A OTHER CCASSES 131-135
! PEAK FORECAST TABLES 136-155 (REQUIRED BY THE ENERGY FACILITIES SITING COUNCIL) f i
4 a 46
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e-i i INTRODUCTION ! AND
SUMMARY
l. 1. 1 s. e De
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t BOSTON EDISON COMPANY
,. PRINCIPAL RESULTS OF THE FORECAST l
l l Sales
- Equivalent Compound l
}^ Actual Forecast Growth Race (%) l 1979 1989 1979-1989 I l , Rn,idential Class
> l Average Number of Households ** 486,368 555,871 1.34 , Average Use per Household (kWH) 5,340 5,288 -0.10 i Total Sales 2,597 2,888 1.07
~ Commercial Class Sales 4,550 5,964 2.74 r-Industrial class Sales 1,758 2,09 3 1.76 Street Lightina Class Sales 125 148 1.70 Railroad Class Sales 21 224 26.71 Wholesale for Resale (Total Requirements) 460 306 -3.99 Total Sales 9,524 11,624 2.01 t' Territorv Output 10,475 12,647 1.90 Annual Peak Load (Megawatts) 2,002 2,534 2.38 4 l' Annual Load Factor 59.7 57.0 -0.4 1
, *All sales in gigawatthours except average use per customer.
, . **Does not include 43,789 master metered apartments which have~their energy reported under Commercial.
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- COMPARISON WITH PREVIOUS FORECAST Territory Territory Total Sales (Gigawatthours)** Peak Load (Megavnets)
[" _ Previous Forecast This Forecast Year Previous Forecast This Forecast , 1979 9,589 9,524* 2,094 2,002 1980 9,621 9,579 2,101 2, 09 1 i 1981 9,868 9,759 2,157 2,130 1 1982 10,221 10,037 2,239 2,193 1983 10,668 10,202 2,320 2,233 f 1984 10,826 10,410 2,355 2,277 1985 11,258 10,667 2,457 2,332
. . 1986 11,869 10,863 2,596 2,374 1987 12,261 11,096 2,686 2,424 r- 1988 12,686 11,377 2,782 2,482 1989 13,108 11,624 2,878 2,534 1990 13,525 11,916 2,973 2,596
- Actual I **The territory sales include sales to the following classes: residential, commercial,
, industrial, street lighting, railways, and the three municipals (Norwood, Wellesley, and Concord) . Territory output would be the territory sales plus losses. System sales would include territory sales plus all other sales for partial requirements, contract sales and NEPOOL interchange. System output would be system sales plus system losses. i.
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- THE BOSTON EDISON ENERGY FORECAST 1980-1989 T'
! INTRODUCTION
, This document presents a forecast of the demand for electrical energy within
\
the Boston Edison territory service area for the period 1980 through 1989. It is intended to provide an input to the planning and decisien-making process re-laced to the scheduling of facilities. It describes the assumptions and f i g methodologies used to develop the forecast for the Boston Edison territory and contains tabulations of the elements of the forecast. 1 I. i I The introduction presents the general results and outline. The succeeding pages show the flow charts of the forecast methodology, a short overview of each sector i. ] and graphic presentations of the forecast's major elements. i . j Over the ten-ycar forecast period (1979 to 1989) electric energy usage is ex-
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[, pected to grow at an equivalent compound race of 2.0%. Usage by the Residential Class will increase at an annual compound growth rate of 1.1%, Commercial at 2.7% and L Industrial at 1.8%. Over the same period, the annual peak load is forecast to
- grow at a rate of 2.4%.
1
- The forecast of total electric energy use is made by projecting energy consumption l !
(, for each customer class and then aggregating the class Tesults. The forecasting
. methodology is different for each class due to differences in the factors affect-ing energy use for each type of customer and the availability of forecasting data.
j l. The forecast is presentec in the following format:
!I a 1. Introduction and Summary i
- 2. Major Sectors
[ a. Demographics
- b. Residential Class Energy Sales
- c. Consnercial Class Energy Sales
-- d. Industrial Class Energy Sales
- 3. Other Sectors f a. Street Lighting Class Energy Sales
, . . b. Railroad Class Energy Sales i i c. Municipals Class Energy Sales I- d. Losses and Company Use
- e. Price Forecast f f. Other Factors
- 4. Peak load Forecast i .
1
- 5. Tables, Charts, and Graphs (EFSC Requirements) i i i f.
The technical appendices which appeared in the April 1,1979 filing will be t I contained in a separate document. 1 4 i e i
SUMMARY
! t 4 i In order to provide information for use in the generat4cn and transmission planning areas of the Company, a forecast of both electrical energy consumption 1 1 i and peak demand is required. The energy forecast is made for distinct classes of customer usage: Residential, Commercial, Industrial, Street Lighting, Railroads, a L. d i !
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Boston Edison supplies electrical energy to 40 cities and towns in the Greater Boston area. A map of the t* ritory is shown on the cover of this document. The Company's territory is contained within Middlesex, Norfolk, and Suffolk counties which are later referred to as the "tri-county area".
i i Wholesale for Resale (Concord, Norwood, and Wellesley), and Lasses and Company Use. The forecasts by class are then aggregated to provide a total energy l 2 i forecast . An energy forecast by itself is not sufficient for facilities planning
- I
{ and must be supplemented by a second forecast of the rate per hour of energy 1
. consumption called the demand forecast which is typically measured in megawatts.
l j The Company is confident that this forecast represents the single best estimate I of the future energy and demand requirements of the Company's service territory. It is the judgment of the Company forecasters that all historical and forecasted I ( dependent and independent variables were based upon the best data available to the Company and upon reasonable statistical methodologies. , i. I J i l i I t k i, l f t i (
> s Energy is measured in kilowatthours and its multiples; 1000 watthours = 1 kilowatthour,1000 kilowatthours = 1 megawatthour,1000 megawatthours = 1 gigawatthour.
1000 watts = 1 kilowatt, 1000 kilowatts = 1 megawatt. The single highest hourly usage in the year is called the peak demand. The ratio of average demand (annual
.. energy divided by 8760 hours) to peak demand is called the load factor.
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RESIDENTIAL CLASS FORECASTING METHODOLOGY The Flow Chart on the next page is a simplified representation of the residential forecasting methodology. (For a more elaborate discussion of this Flow Chart, 7 i please consult the relevant main chapter.) I
;t In the Flow Chart, note that population determines household estimates which in r.
turn determine the quantity of appliances on line. Residential electric energy consumption is then the product of the quantity of appliances, their efficiency, j , and usage, after inclusion of the effects of alternate energy, conservation, price I' effects and new technology. j . Residential contribution to peak is equal to the product of residential electric 1 ; energy consumption times the share of that consumption which occurs at the time 4 of system peak demand. 1 i t The share of a class' consumption which occurs at the time of system peak demand is called the peak factor for the secto.. Peak factors are used for each class - residential, commercial and industrial. t 0 I k. t s. l m W w
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s ; ' RFSIDINTI Al. B.NERGY OCSlHrTION , i
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SERIES Il sf g f h FERTILITY M RIRTNS - NuuSEH0lb NOUSEllul D % SATURATl0N SA1URATIONS 1972 APPLIANCES J END FURMATION TRENDS } ESTIMATES TREND DEVEl.DPED FROM THROUCN ) ON-l.INE IUCN l i NEr001 tt0 del. 1990 Tv as I T e h SURVIVAL
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q DEATNS _ DOE 1985 POTENTIAL ArrLIANCE h INFANT EFFICIENCY CUIDELINES m I ) SURVIVAL RATES
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1972 & 1975 ASINUAL AFFLIANCE US & LOCAL IDMG RUN PRICE ELASTICITY h ENERGY USACE ESTlHATES ENERGY USE PER APPLIANCE SURSTITUTION IMPIAYNENT HICRAfloll - jg . GRIMTN gj 5HORT RUN g %g se
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PRlrE RESIDENTIAL / ELECTRIC \ FORECAST DEDUCT JNERGY USE ENERGY l OF RATES C. C-1 & Ke , . CONSlHPTION Al. TERNATE
/4 ENERGY CONSERVAT'Olt NEW TECHN01DCY
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TlHE OF ~~~~~~~~~~~3 RESIDENTIAL USE RATES 7 CONTRIURTION TO FEAK TilEY ARE MupEl. LED IIERE AND TRANSFERRED.
- RATES C.C-l AND K ARE RESIDENTIAL. IN CalARACTERISTIC, RUT RY BATE S1RUCTURE CuttlERCI AL.
e f CCNMERCIAL CIASS FORECASTING METHODOLOGY The Flow Chart on the following page presents the Commercial Forecasting Method-ology. First, using econometric methods, a forecasting equation was estimated. ( This equation relates commercial energy consumption to Gross State Product, lagged typical commercial electric bill, residential households and commercial customers. The Company's Commercial class is not homogeneous and contains a large variety of business establishments. Therefore, explanation of consumption behavior requires several variables. Gross State Product captures the browth in economic activity of the business sector over time, residential households and the number of com-mercial customers indicates the level of demand within the service area, while the lagged commercial price variable measures the consercial sectors' sensitivity to changes in average price. 1 Af ter the equation was estimated, forecasts of GSP, price, households and com-i mercial customers were substituted into the equation, yielding a preliminary forecast of electricity consumption. The effects of cogeneration, alternate energy, conservation and new technology were then applied, resulting in the final forecast of Commercial Electric Energy Consumption. Commercial contribution to
' peak is estimated by multiplying energy consumption by the Commercial Peak Factor, f
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INDUSTRIAL CLASS FORECASTING METHODOLOGY l ( Industrial energy is forecasted on a disaggregated basis by 19 two-digit ]
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Standard Industrial Classification (SIC) codes. The same general approach was made use of in forecasting each of the SIC codes. The methodology used is ( presented in general form in the Flow Chart on the following page. The basis
/
t for the forecast is that industrial energy consumption is functionally related
; to economic activity. This is modeled by using energy intensiveness (measured i
in megawatthours per employee) and employment as indicators of economic activity. As shown in the Flow Chart, energy intensiveness and employnent are forecast j 4 from State data. The employment forecast is " mapped" to the Company's industrial ;
) class of customers by applying growth rates for the state to territory specific ;
employment for 1977. Multiplying forecasted energy intensiveness and employment I ( yields a forecast adjusted for any compositional differences that may exist between the state and territory cot cerning employment growth rates. These figures are then f.urther adjusted by the Company's estimates of the impact of alternativa f energy, conservation, cogeneration, and new technology. Forecasts for some SIC's have been adjusted to reflect the Company's specific industry knowledge. This results in the final forecast of industrial electric energy consumption. Industrial j contribution to peak is the product of industrial electric energy consumption and the industrial peak factor. - i.
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l On the following pages are
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graphical presentations of the energy forecasts and the peak loads. s t i
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( TERRITORY ENERGY SALES U3............. ................. . .G. I.G. AWATT. H. OU.. .RS. ................................... . .
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o : o, . . 9968 1972 1976 1980 1984 1988 1992 1996 l TEAR l -
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, e o SUMMER & WINTER PEAK LORD m,,.......................................M,E.GAW.A.T.T.S..,....................................,
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_ c- .._ r-RESIDENTIAL ENERGY FORECAST _ i i r j The residential energy projections were derived from four major components. These consist of: I ( l. the number of households,
- 2. the average amount of electricity consumed per household,
- 3. the displaced energy due to conservation and alternative energy sources along with added energy due to new technology, and
- 4. the real price of electricity.
f^ The number of households was estimated from a detailed demographic analysis which { calculates the population in the Company's service area employing the cohort-survival method of population forecasting. Birth and death rates of the ".S. Census Bureau have been regionalized and the historical data base has been updated for the state; fertility races and trends are in agreement with the most recent
- k. data available. Migration has been estimated through regression analysis which p
relates observed migration parameters to employment growth in the BECo. service area and employment growth in the Nation. I,. Population was converted to households by dividing the population by estimates of the number of people per household. The number of people per household is L based upon national household formation rates as deteriined by the U.S. Bureau of the Census. The demographic module of the NEPOOL model was utilized in cal-culating this information. The average amount of electricity consumed per house-hold was estimated from internal atadies which examined eighteen individual
\
appliance usages and potential guidelines for future appliance efficiencies from t f ( 4 The cohort-survival method is based upon the premise that population in any
- year is equal to the population in the previous year plus births minus deaths and plus or minus any population migration. This calculation is normally done by age and sex.
f f D
r-r the U.S. Department of Energy. The existing saturation of appliances was ( directly calculated from Company specific data which was developed from the ( Company's 1978 saturation survey. Appliance saturations were linked to income and the forecasted appliance saturation levels were based upon expected changes [ in income. A residential forecast was then produced by multiplying households by I f average annual household electric usage. f The residential forecast was adjusted to account for conservation, alternate energy, new technology and the effects of N ice. Dstails of these adjustments are explained in the body of this document. I The resulting residential energy grows from 2597 gigawatthours (actual) in 1979 to 2888 gigawatthours in 1989 (equivalent to 1.1% per year). t COMMERCIAL ENFRCT FORICAST The electr,1 cal energy usage of the Conumercial Class continues to be the most ( difficult sector to forecast because of the non-homogeneity of the size and type i of customer. Consequently, an econometric model was employed to forecast this sector. A priori reasoning and economic theory indicates there should be a ( variable to represent the export serving activities of Boston based Commercial { activity (education, health, insurance, financial, etcJ; a variable to represent commercial activity specifically within the service area; a variable to represent the territory specific household serving component; and a variable to represent the price of electricity. Through sta irtical analysis the following variables (^
.were selected:
i . 5 Appliance saturation is the percentage of homes which have the appliance. 6 To be corsistent with our rate base, the sales to master metered apartments are then subtracted from this estimate and are reported as Commercial Class sales. l t
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- 1. the gross state product,
- 2. the number of commercial customers,
(
- 3. the number of residential households, and
- 4. the lagged real price of electricity.
The equation developed was based on the historic value of the above parameters from 1960 to 1978 and is shown below: f i' SALES = -17724.32 + .02853898 RHH + .1009761 CUST + .02359797 GSP -2.036517LTYPB I WHERE: SALES = Total Commercial Sales [ RHH = The number of residential households t CUST = The number of commercial customers 2 GSP = Gross State Product 8 LTYPB = The lagged average real price of electricity L = Lagged i For this model, GSP was projected to grow at the same rate of growth as employ-i ment. Employment growth was taken from the NEPOOL model. The number of ( residential households was calculated in the demographic section of the j, residential forecast. The number of commercial customers was forecast by race I,. code using regression analysis and specific territory Ehowledge where applicable. The real price projections were taken from a Company forecast of average price per kWH from 1980 to 1989.' The commercial consumption figures from the model were adjusted for conservation, new technologies and long-run price effects. ( The value of this variable does not include sales from Rates C, C-1 and K. These rates are modeled within the residential sector due to their characteristics. 1. 8 The average real price of electricity was " lagged" one year. 9 I The price forecast is contained in a later chapter of this document.
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The rebulting commercial energy growth projection is from 4550 gigavatthours (actual) in 1979 to 5964 gigavacchours in 1989 (equivalent to 2.7% per year).
! INDUSTRIAL ENERGY FORECAST
. The industrial methodology is similar to the previous filing with the exceptian that it is more service area specific. Employment data by SIC has been collected for cities and towns within the service area from records at the Division of Employ-a{
ment Security (DES). A growth rate was calculated from the NEPOOL data for f 1970-1980 and applied to 1977 territory specific employment. A measure of energy intensiveness (kilowatchours per empJr.yee) for the state by SIC was developed ( from the NEPOOL model. The growth in this measure was applied to actual energy
- intensiveness calculations for our service area. The product of employment and energy intensiveness by SIC results in a forecast of industrial energy. This forseast is then adjusted for conservation, new technology and cogeneration in order to produce a final forecast.
(' Industrial energy is projected to grow from 1758 gigawatthours (actual) in 1979 ( co 2093 gigawatthours in 1989 (equivalent to 1.8% per year). i i STREET LIGHTING, RAILROADS AND RESALE CLASSES Street Lighting - Crowth in installation of street lights within the BECo. service area was provided by the Commercial Department for 1980 to 1985. The growth is expected to remain constant at 1980-1985 levels for the period 1986-1989. lf 1
- Sales to street lighting are expected to grow from 125 gigawatthours (actual) )
i i ; in 1979 to 148 gigawatthours in 1989 (an equivalent 1.7% per year). ( i
\
s. l L
v-Railroads - Sales to the MBTA (Massachusetts Bay Transportation Authority) are assumed to be constant from 1981 through 1983. Thereafter it is expected that the MBTA will cease their present generating capability and purchase bulk re-t I quirements from the Company. The electrification of AMTRAK is forecasted to require the Company to begin supplying electric requirements in 1984. In this case, AMTRAK expected usage was supplied by their engineering consultants. The railroad electric consumption is expected to increase from 21 gigawatthours (actual) in 1979 to 224 gigawatthours in 1989 (an equivalent 26.7% per year). I Resale - The towns of Concord, Norwood and Wellesley presently purchase their j total requirements from the Company. Each town is required to submit an estimate ( of its future requirements to the Company. The requirements of each town are analyzed separately and then combined to furnish projected total energy sales figures for this category. The town of Norwood may not remain a customer by mid 1983. For the purpose of this forecast, we have assumed Norwood will still purchase 6'0% of their requirements in 1981 and 1982. In 1983, they will purchase 60% of their requirements durLng the first six months of the year after which service to Norwood will terminate. Sales for resale then are expected to decline from 460 gigawatthours (actual) in 1979 to 306 gigawatthours in 1989 (an equivalent
; -4.0% per year) .
( __ LOSSES AND COMPANY USE This category represents energy usage inherent in the transmission and distribution of electricity. Use is expected to be at a level of 8.8% of total sales as determined by an internal study. This category is expected to grow from 951 gigawatthours in 1979 ( (actual) to 1023 gigawatthours in 1989 (an equivalent growth rate 0.7% per year). L.
7
. .. ,e l
1 PEAK LQAD The peak load is calculated by using peak factors for each customer class. l These factors are developed by calculating the ratio of the class coincident 0 to the annual energy sales of that class. The coincident demands of demand all classes are then summed to obtain the territory peak. The peak factors are developed by using recent load research information from the Company Cost-of-Service studies and territory specific data. t The summer peak is expected to increase from 2002 megawatts (actual) in 1979 to 2534 megawatts in 1989 (an equivalent 2.38% per year). MISCELLANEOUS TOPICS I This section summarizes the approach taken to incorporate into the forecast the ( effects of electricity prices, TOUR, conservation, alternate energy, cogeneration and new technologies. L Price Forecast The forecast of the real average price of electricity is based upon the future base revenue requirements of the Company and the estimated cost of fuel. The forecasted average prices have been deflated by the Consumer Price Index to
! obtain the real price. The complete forecast and explanation is contained in the text of the forecast. A graph showing the average real price of electricity for 1979 to 1989 is on the next page, i The real average price is projected to increase from 5.41c per kilowatthour in 1979 to 5.99c per kilowatthour in 1989.
i OThe class ccincident demand is the demand in megawatts of that class at the time of the territory peak load. The Siting Council requires that the coincident peak of each class be estimated. i
)
l
- l
V l l o O FORECASTED PRICE OF ELECTRICITY
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .I.N. . R. E. A. L. . T. ER. M. S. . 1. 9. 78. .1.0.0. . .... . . . . . . . . . . . . . . . . . . . . . . . . . .
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Time-of-Use Rates We have calculated a potential 32 megawatt reduction in territory peak demand 1 in 1989 if TOUR, as presently under consideration by the Massachusetts Department i of Public Utilities, is implemented. However, in view of the fact that the TOUR l proposals have not been acted upon, the Company did not consider it appropriate ! to reduce the forecasted peak loads by an estimated TOUR implementatica impact. s Conservation I Price induced conservation has been accounted for in each major class by price elasticity adjusrments to the expected energy consumption. In addition, the Company has endeavored to quantify the results of the policies cf the Federal government and also those of the Commonwealth. These are generally non-price I induced conservation reductions in electric consumption. The forecast has been
, reduced by the estimated developed. If, in fact, price is related, the total conservation impact may be overestimated.
An estimate of the Department of Energy appliance efficiency goals have been [, l , applied to the residential sector. The residential consumption has also been
! reduced by some other factors such as replacement of future electric resistance heating by heat pumps, supplemental heating produced by wood stoves and reduced hours of air conditioning. Microwave ovens are expected to reduce electric energy consumption of electric ranges by a factor of three times their own
(_ usage, i.e., for each kilowatthour expected to be used by microwave ovens the (., usage of electric ranges is reduced by three kilowatthours. The overall reduction in the residential sector due to all the above actions is approximately 1,100,000
- megawatthours (about 27%).
i l wa
l 0
. . . .o The Company has avamined and quantified energy savings due to the following programs and policies of the Conanonwealth of Massachusetts.
- 1. Lighting Standard Revision
- 2. Thermal Efficiency Standards
- 3. Enargy Conservation Extension Service
- 4. Public Education and Information Program i 5. Reduction in Temperature Standards
- 6. Reduction in Ventilation Standards
- 7. Public Housing Improvements I 8. Weatherization Program Information on these programs and policies was obtained from the Massachusetts
' Energy Office and the Massachusetts Building Code Conunission. As a result of I this analysis, the forecast has been reduced by approximately 135,000 megavnethours by 1989.
- Graphs showing the impact of conservation of each of the three major sectors are on the following pages.
( i w h t l
V 9 i O RESIDENTIAL:CONSERVA. TION EFFECTS O ............................ m.............. ......................G.I.G.AWATTHOURS..
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- 1 F
1 i l a 8 COMMERCIAL: CONSERVATION EFFECTS
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O C INDUSTRIAL: CONSERVATION EFFECTS i, ru. . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . .C.I.G.A.W.A.T.T.H.O U. R. S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . m . 4 . . . . ( O . . . . . C3
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. 9978 1980 1982 1984 1986 1988 1980 1992 YEAR
p ** s1 4 I Alternate Energy Hydroelectric, biomass, wind and photovoltaics are estimated to have a negligible I '
, impact over the next ten years. It has been estimated that there are nineteen 4
industrial customers that could potentially cogenerate. Of the nineteen customers j only two have a steam demand capable of sustaining a cogeneration plant. There-1 ! fore, we have reduced the forecast in 1981 by 21,681 megawatthours (for the two
- currently able to cogenerate) and 216,814 magavatthours in 1990, assuming every 1
customer will cogenerate if possible. Estimates of solar space heating and hot ; ( water heat.fug have been developed by in-house experts. M a result, the forecast i has been res tend by 5,400 megawatthours in 1989. Our best estimate of the effect of the Harvarr Medical Complex (MATEP) is a loss of 10,000 megawatthours in 1981 f{ 1 l and 20,000 megawatthours in 1982 and beyond. I New Technology This year, the Company has incorporated the expected impact upon the forecast of t i several developments in new technology. Studies were undertaken within the 1 8 I i Company to assess the impacts of technological advances that might result in an J
}
I affect on energy consumption. The following represent our effort. i
. The effect of electric vehicles is expected to be felt during the next ten years.
f A study was performed by Company personnel that estimates approximately 5,260 I electric vehicles within the BEco, service territory by 1989. By 1989, it is 1. expected that electric vehicles will consume .5 kWd per mile or recharge energy. [ Each electric vehicle is assumed to be driven approximately 8,000 miles per year. Residential energy is increased by 21,040 megawatthours in 1989 due to electric 4 L vehicles. There are devices which are intended to make induction motors more l
; j energy efficient such as the Nola Power Factor Controller, the Alternating Current Synthesizer, also the Wanlass the Gould's E-plusR high efficiency motors. These controllers are expected to be relatively inexpensive and, therefore, attractive t
j ,,
e p *e ,s e to boih industrial and commercial establishments. These controllers and efficient ' m tors are expected to reduce the forecast by 48,000 megawatthours by 1989. I Inkjet printers or non-impact printers are expected to consume approximately 60% less energy than an Lapact printer. This constitutes a sizeable reduction in the ( printing machine's operating costs, which should serve to fuel their industrial [ adoption. It is expected that adoption of inkjet printers will reduce the forecast
; by 13 megawatthours in 1989.
t I I i ( ( i
?
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* *o J 1 1 1
MAJOR CHANCES IN FORECASTING METHODOLOGY The major changes in this year's forecast are:
- 1. The migration equation has been reestimated with the acquisition of an
( additional year of data, f
- 2. The appliance efficiencies have been altered. The DOE has not set any
{ specific guidelines for the efficiencies but they have stated that the 1985 appliances would be at least as efficient as the most efficient appliance in 1979, which is the approach used in this forecast.
- 3. The Commercial forecast equation has been reestimated using econometric
, methods.
l I- 4. We have introduced a "shif t share" technique in the industrial employment forecast through the use of weighting factors.
- 5. The impact of New Technologies, such as electric vehicles, efficient motors and inkjet printers, have been quantified for this forecast.
i
- 6. The effects of solar and cogeneration on the forecast have been updated.
- 7. Wood stove use reduces future electric heat usage in the residential sector.
(. l. L.
- 29A -
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t a 9 0 i DDf0 GRAPHICS I l t I l DW G
i Demographics Summary I This year's filing of Boston Edison's long range forecast specifies a
- compound annual growth of 1.2% in households over the next 10 years - 599,660 households in 1989. The actual (1970 - 1979) and the forecast (1980 - 1990)
Boston Edison households are shown in the accompanying table, Table 1. The , J assumption is made that 100% of the households use electricity, therefore, each household is assumed to be a customer. l Population and household forecasts are the result of the regionalization The i of birth rates and death rates from the U.S. Bureau of the Census. j [ i fertility rate and trend have been updated and regionalized for the service
*~
area. These updates are the result of the most recent information available. This year migration is related to territory employment growth, developed by town, and national employment growth. f The NEP00L long range forecasting methodology is the instrument used for providing the population of the Company's te-ritory prior to adjustment for migration. The model also provides data for household formation trends, which were then used to convert population into number of households. This methodology
, is presented in the flow chart in Figure 1.
( A methodology has been formulated for forecasting migration based on territory employment growth and national employment growth. Assumptions were made about the type of growth patterns Boston is expected to face in the near future. Sources
- representing many local and regional agencies in Boston all agree that development activity initiated during the past decade promises
' to come to fruition and provide the momentum for growth and expansion in the 80's. This growth can only be translated into growth in employment, growth in population and growth in housing.
*1. "1980 Outlook is Bright for Boston," Boston Sundav Globe, December 30, 1979, P. C1.
- 2. The Outlook for Boston: Development in the 80's Boston Redevelopment Authority, September,1979. __
Past, Current and
- 3. Margaret C. O'Brien, Boston's Population and Housing:
Expected Future Growth through the year 2000, Boston Redevelopment l
- Authority Research Department, December,1979.
- 4. Richard D. Hill, First National Bank of Boston, Focus '80: The Regional Economic Outlook. Panel discussion given at Copley Plaza on November 27, 1979, sponsored by Greater Boston Chamber of Commerce .
- 5. Jane C. Martignoni, Regional Agencies Overview: 1980-89 Economic Forecast,
Task - F22, January,1980 Boston Edison.
- 6. " Boston is Ready for New Hotels," Boston Sunday Globe, February 17, 1980, P. Fl.
- 7. "New England Commercial and Industrial Review," Supplement to The Boston
. _' , Sunday Globe, March 11, 1980.
i s
i Table 1 Boston Edison Company Residential Households - 1970-1990 Year Actual Forecast & Growth 1970 485,254 1971 487,350 1972 499,712 1973 509,099 1974 516,634
' 1975 519,159 f 1976 518,879 1977 520,890 1978 524,472
. 1979 530,157
. 1980 537,766 1.44
- 1981 545,785 1.49 1982 553,412 1.40 l 1983 560,739 1.32 1984 567,837 1.27 J 1985 574,801 1.23 1986 581,117 1.10 1987 587,367 1.08 1988 593,549 1.05 1989 599,660 -
1.03 1990 605,71C 1.01 Compound annual growth 1979-1989 is 1.2% t. e
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'The technical description and data base of the NEPOOL model demographic sector will be contained in a separate document. The development of territory specific migration will also be contained in a separate document.
The primary input needed to forecast residential energy consumption is a projection of the total number of households expected to be on-line in each year of the forecast period - 1980 to 1989. This household number comprises single family homes and apartments. This projection of the number of house-hoids is accomplished by first projecting future population levels in the re- I tail sales area, and then utilizing household formation trends to determine the j number of households. , Changes in population occur as a result of bn.eths, which increase the popu-lation, deaths, which decrease the population, and migration which may increase or decrease the population level. Population changes can be divided into two components, i.e., the natural increase component and the migration component. Natural increase is simply the number of births minus the number of deaths applied to the current population figure. That is, the population of a region or state in any ote year is determined by the addition of natural increase by births to the population surviving from the previous year, less the natural decrease due to deaths in that year. The migration component represents mobility or movement of the population; i.e., the population flow that moves into or out of an area. The impact from the migration component is much more difficult to determine. 4 - S i 1
The ,following equation illustrates population change:
+ BIRTHS A,t - DEATHSA,S,c I ^ A,S,t A.S.t+1 " A.S.t Where POP = Population by age and sex in year t+1 A,S,t+1 POP = Population by age and sex in year t A,S,t BIRTHS = Births by age of mother in year t A,t DEATHS = Deaths by age and sex in year e AgS,e MIGRATION g
= Migration by age and sex in year t In population forecasting, a common method employed is the cohort survival method where whole cohorts are aged through time. A cohort is a group of people born in the same time period. In this forecast the time period is a five-year age interval broken down as follows: .
Population aged 0 to 4 40 to 44 5 to 9 45 to 49 10 to 14 50 to 54 U to 19 55 to 59 20 to 24 60 to 64 f 25 to 29 65 to 69 30 to 34 70 to 74 35 to 39 75 + Each of these five-year age cohorts can be thought of as five one-year age cohorts being aged through time. A The migration component is the movement of persons from one geographic area to another. Migration must always be considered, along with the natural increase method, to reliably account for the growth or decrease in a population. APPROACH AND METHODOLOGY
- There are thousands of calculations necessary for a population and house-hold forecast. To avoid hand calculations it was dEtided to employ the demo-graphic module of the NEP00L model and have the model perform the calculations af ter our review of the data base. However, past experience has shown that the migration module of the model does not perform well for the Boston Edison service territory even though the model does extremely well at the state level. Therefore, we simply disconnected the migration module and had the model calculate the population of the Company's service territory based upon birth and death rates only. The result is shown in Table 2.
l The difference between the model's 1977 estimate and actual figures from the 1977 estimates is 79,011. As we have fully accounted for births and deaths, this number must reprasent c':mulative out-migration since 1970. This migration is the cumulative difference because the model begins with the actual 1970 Census count.
*It is suggested that frequent referral to the flow chart contained in the l Demographic Summary will be an aid in understanding this section.
l
'The population numbers can be adjusted for this migration by subtracting the 79,011 from each year beyond 1977. The result is a population forecast adjusted for migration that has occurred up to and including 1977, but has not yet had future estimates of migration considered. The result is shown in the right hand column of Table 3. The 1970 Census count and 1977 estimates are shown in Table 3 .
In determining migration, it was postulated that it is related j to the local employment growth and national employment growth. Boston Edison employment growth is known historically and tri-county (Norfolk, Middlesex, and l 1 Suffolk) migration can be estimated. Migration =a+b Boston Edison Territory - b U*S*
! tri-county y 2 Employment Employment Growth Rate Growth Rate ' The Boston Edison territory migration can then be estimated as the proportion of territory population to tri-county population. Statistically the migration equation turned out to be reasonable. The estimated migration is shown in l Table 4. The population forecast that accounts for all migration since 1977 1s shown in the right hand column in Table 5 . Cumulative migration is subtracted from the adjusted population shown in Table 2. The technical discussion of l territory migration is contained in a separate document.
The population can be converted to househcids by the use of forecasted esti-mates of people per household. This ratio was determined by the method shown I in the flow chart. The state population was converted to people per household via national household formation trends. The NEPOOL Model was used to generate these numbers. In addition, the number of people per household generated in this manner was compared to estimates developed by the New England Energy
! Congress a .d found to be reasonable. The two sets of numbers are shown in Table 6.
l The number of people per household can be divided into the population fore-cast to determine the total number of bouseholds in Boston Edison Territory. This step is shown in T&ble 7.
' A test of the reasonableness of the household forecast can be made by com-paring the results with actual historical figures. 7his historical household count f or the Company's service territory is shown in Table 8.
The forecasted household count is 10,497 households higher than the actual count in 1979 as shown in Table 9. To bring the forecast in line with the actual count, the 1979 differential of 10,497 households was subtracted from all years beyond 1979. This adjustment produces the final forecast of resi-dential households which is shown in the right hand column of Table 9 and in the table in the summary.
. - ~ -
c. 1 ( i TME 2
' Adjusted Population - Comparison of NEPOOL Population and 1977 Population Estimates Adjusted Year NEPOOL 1977 Estimates
- Difference Popula tion 1977 1,632,740 1,553,729 79,011 1,553,729 1978 1,635,838 1,556,827 1979 1,639,385 1,560,374 1980 1,643,419 1,564,408 j 1,568,963 1981 1,647,974 1982 1,652,575 1,573,564 1983 1,657,250 1,578,239 1984 1,662,029 1,583,018 j
. 1985 1,666,932 1,587,921 1986
- 1,671,977 1,592,966 f 1987 1,676,877 1,597,866 l 1988 1,681,627 1,602,616 1989 1,686,217 1,607,206 1990 1,690,637 1,611,626
- Current Population Reports, P-25, No. 834, November 1979 I
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' TABLE 3 i BOST N EDISON COMPANY RETAIL SALES AREA POPUIATION BY CITY AND TNN i$ Actual
- Actual ** Forecast 1977 j l 1970 1977
<- Acton 14,770 18,707 a Arlington 53,524 49,303 Ashland 8,882 8,837 13,577 j Bedford 13,513 i Bellingham 13,967 14,776 Boston 641,071 618,493 4
Brookline 58,699 50,680 Burlington 21,980 24,726 i 4 Canton 17,100 18,299 Carlisle 2,871 3,310 } Chelsea 30,625 24,312 j Dedham 26,938 26,587 l
. Dover 4,529 4,987 Framingham 64,048 64,079 Hollis ton 12,069 13,176 Hopkinton 5,981 6,682 Lexing ton 31,886 32,384 Lincoln 7,567 7,586 f Maynard 9,710 9,845 ,. Medfield 9,821 10,411 j
Medway 7,938 8,2 19
.- Millis 5,686 6,770 l
Milton 27,190 27,281
' I Natick 31,057 30,596 Nee dham 29,748 29,607 Newton 91,263 89,183 Norfolk 4,656 6,545 Sharon 12,367 13,962 Sherborn 3,309 4,265 Somerville 88,779 76,771 '- Stoneham 20,725 21,575-Sudbury 13,506 15.128 Walpole 18,149 18,717 j 61,582 55,632 4
Waltham Watertown 39,307 34,927 Wayland 13,461 13,021 Weston 10,870 11,696 Westwood 12,750 13,970 Winchester 22,269 22,449 i Woburn 37,406 34,658 1,601,559 1,553,729 1,632,740 i, The 1977 Forecast differs from the 1977 Actual by 79,011 t.
- Current Population Reports, Series P-25, No. 669, May 1977
** Current Population Reports, Series P-25, No. 834, November 1979
- 37 _
i
r~ f~ l ( l t i i Table 4 Migration for Tri-County and BECo. Areas _ Cumulative Tri-County BECo BECo Migration Migration Migration BECo Development Development Development Population 1978 -24495 -14036 -14036 1542791 1979 - 7075 - 4054 -18090 1542284 1980 - 7075 - 4054 -22144 1542264 j - 3463 -25607 1543356 g 1981 - 6043 1982 - 6043 - 3463 -29070 1544494 1983 - 6043 - 3463 -32533 1545706 1984 - 6043 - 3463 -35996 1547022 {. - 6043 - 3463 -39459 1548462 1985 1986 * - 5821 - 3335 -42794 1550172 1987 - 5821 - 3335 -46129 1551737
, 1988 - 5821 - 3335 -49464 1553152 1989 - 5821 - 3335 -52799 1554407 1990 - 5821 - 3335 -56134 1555492
- 3002 -59136 1556748 l.
1. 1991 1992 - 2668 -61804 1558005 1993 - 2335 -64139 1559216 f 1994 - 2001 -66140 1560316
' 1995 - 1668 -67808 1561251 1996 - 1334 -69142 1562041 1997 - 1001 -70143 1562661 1998 - 667 -70810 1563073 1999 - 334 -71144 1563294 2000 0 -71144 1563319 l 6..
1
$ h -- .
r F t' Table 5 Projection of the Population in BECo Sales Ares Cumulative Adjusted BECo BECo I I Year Population Migration Population i. 1978 1556827 -14036 1542791 1979 1560374 -18090 1542284 1980 1564408 -22144 1542264 1981 1568963 -25607 1543356 1982 1573564 -29070 1544494 1983 1578239 -32533 1545706 1984 1583018 -35996 1547022
< 1985 1587921 -39459 1548462 1986 1592966 -42794 1550172
- 1987 1597866 -46129 1551737 1988 1602616 -49464 1553152 i 1989 1607206 -52799 1554407 l 1990 1611626 -56134 1555492 1991 1615884 -59136 1556748 1992 1619809 -61804 1558005
[- 1993 1623355 -64139 1559216 1994 1626451 -66140 1560311 1995 1629059 -67808 1561251 1996 1631183 -69142 1562041 1997 1632804 -70143 -- 1562661 1998 1633883 -70810 1563073 t 1999 1634438 -71144 1563294 2000 1634463 -71144 1563319 j { i l l .. I
. .. . .. I
-- j l
1 i q-e i ?
] -
r ( I TABI.E 6 i~ PERSONS PER HOUSEHOLD IN MASSACHUSETTS: 1976-1990 ] Year BECo NE Energy Congress 1 - 1976 2.99 2.95 1977 2.94 2.93 1978 2.89 2.86 1979 2.85 2.81 1980 2.81 2.77 f 1981 2.77 2.73 I 1982 2.74 2.69
. 1983 2.71 2.64 j 1984 2.67 2.60 1
1985 2.65 2.56 f 1986 2.62 -- 1987 2.60 -- 1988 2.57 -- 3 1989 2.55 -- 1990 2.52 2.46 Source: Preliminary Report for Public Review," New England Energy Congress, November 1978. i L r {
P r
\ , - Table 7 Projected Number of Households 1978-2000 BECo People / House Proj ectad I
Year Population hold Ratio BECo Households f 2.939103 78 1542791 2.894899 532934 79 1542284 2.852626 540654 80 1542264 2.812999 548263 81 1543356 2.774415 556282
' 563909 i 82 1544494 2.738905 83 1545706 2.705898 571236
- 84 1547022 2.674964 578334 85 1548462 2.645596 585298 86 1550172 2.620241 591614 i 87 1551737 2.595467 597864 88 1553152 2.571247 604046 89 1554407 2.547554 610157 J~
90 1555492 2.524298 616207 91 1556748 2.504687 621534 92 1558005 2.486704 626534 93 1559216 2.470313 631182 94 1560316 2.455729 635376 95 1561251 2.441574 639445 96 1562041 2.427918 643366
; 97 1562661 2.415862 646834 98 1563073 2.404262 650126 99 1563294 2.393196 653224 ; 2000 1563319 2.381706 656386 1
I
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TABLE 8 . BOSTON EDISON COMPANY RESIDENTI AL 110LISEll0LDS - 1970 TO 1979 RESIDENTI AL RATE STRUCTURE Year Total B-020 B-021 B-022 B-023* C C-1 K** 1970 485,254 452,405 3,630 4,945 9,245 2,650 12,379 1971 487,350 449,409 4,463 6,018 11,081 4,000 12,379 1972 499,712 454,836 5,782 7,495 14,120 5,100 12,379 e n 1973 SPT,099 459,360 6,642 8,729 14,539 7,450 12,379 s 1974 516,634 461,189 7,490 9,438 549 15,489 10,100 12.379 1915 519,159 460,807 7,839 8,757 2,524 16,089 10,746 12,379 1976 518,879 45b,193 8,591 9,120 3,108 17,019 10,469 12,379 1977 520,890 456,d10 9,270 9,623 3,830 18,999 10,779 12,379 1978 524,472 457,053 10,189 10,163 4,652 19,994 10,042 12,379 . 1979 530,157 459,249 11,060 10,821 5,048 20,647 10,136 13,003
- Rate B-023 was begun in 1973. In that year, new customers on this rate were summed with rate B-020.
** Verbal documentation f rom Boston llousing Authority.
f Table 9 Actual Households 1970-79 & Projected Households 1980-2000 (Adjusted) [. Projected Actual Adjusted BECo BECo BEco HH Year Households Households Projections t- 1970 485254 1971 487350 l 1972 499712 1973 509099
! 1974 516634 1975 519159 1976 518879 1977 520890 1978 532934 524472 1979 540654 530157
, 1980 548263 537766 1981 556282 545785 1982 563909 553412 1983 571236 560739 1984 578334 567837 1985 585298 574801
, 1986 591614 581117 1987 597864 587367 1988 604046 593549 4 1989 610157 599660 1990 616207 605710
, 1991 621534 611037 1992 '626534 616037 1993 631182 620685 1994 635376 624879 1995 639445 628948 1 1996 643366 -- 632869 1997 646834 636337
- 1998 650126 639629 1999 653224 642727 2000 656386 645889 l
t { t i l t 6
f P Q , O RESIDENTIRL HOUSEHOLDS 2.. ..... .... . .................... . ........................ . ...... ...... . . ... Q . . . O , . . . . . o .
. O l *1979-530.157 .
00 ... . . . . . . . . . ...........>. . .. .... ...... ..........................s.............. m . 7 [ c O o . . . . . . C. ..... . ... ........... ........... .. ........... . . . . . . . . . . . . ............. ............. . 2 . . . . . . O . . . . . . o 4 O . . . . . . r C3. ..... . . . . . . . ...........s............ ............s...................... ..s............. y . . en . . . . . . . Q xo . O O * * *
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Forecasts. . . . % . r . . l o . O . e . . . . . . . o 1 t i @. ... . . . . . . . .,........... ........... .............. . . . . . . . . . . . . .,........... .. . ..... O . . . . . . . o . O. o
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O . . . . . . . O . I 5 5 5 4 4 5 9968 1972 1976 1980 1984 1988 1992 1996 TERR
- 44 -
# # 8 ,4 k
$ 9 9 t 1 RESIDDrrIAL t. t t I s S
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R, i 1 Residential Forecast i Summary . The residential portion of the forecast reveals a compound annual growth of j 1.07% increase in energy consumption from 2597.4 gigawatthours in 1979 to 2887.8 gigawatthours in 1989. The actual (1970-79) and the projected (ISSO to 1989)
- l. amounts of energy consumption are shown in Table 1.
The usage per household is calculated by estimating the electric energy con-1 sumption of nineteen appliances. Electric energy consumption is calculated sepa-
- rately for each appliance and the results aggregated. The numbers of each appliance I
for each year of the forecast are estimated by combining the results of the i Company's 1978 Appliance Saturation Survey with the NEPOOL forecast of appliance j saturation levels for each year. The resulting appliance saturation forecast is 1 then applied to the household forecast to determine the projected number of each j appliance for each year. Total residential electric energy consumption is the product of the quantity of appliances, their efficiency and usage, adjusted for the effects of alternate { energy, conservation, and price effects. A flow chart depicting the individual J , j steps of the methodology is shown on the following page. The appliances considered in this forecast include:
}
j Electric Range Clothes Washer Refrigerator-frost free Electric Dryer Refrigerator-standard Electric Water Heater 4 Freezer-frost free Microwave Oven Freezer-standard TV-color Dishwasher TV-Black / White l I Room Air Conditioner Electric Space Heating ] - Central Air Conditioning Heat Pumps l Lighting Wood Stoves
' I, Miscellaneous Methodology The following equations are used to calculate the Basic residential class energy consumption:
I Energy by appliance = Number of appliances
- energy per appliance Total energy = Sum of energy by appliance l Energy per appliance per household = Energy by appliance Number of households Energy per household = Sum of energy per appliance per household Appliance Number Following the development of future households in the Demographic Section, the number of appliances on line is calculated. During 1978 the Company sponsored a survey of its residential customers to determine the saturation of appliances in the service area. Saturation of appliances refers to the percentage of households owning a given appliance. Saturation data from this survey is used, along with other inf ormation, to produce the number of appliances in the territory.
e
e . '. ,, e d l TAB 12 1 4 l Residential Energy Forecast 1980-1990 in Gi8avatthours Forecast % Change Year _ Actus1 8.5 1970 2149.2 6.0 1971 2278.1 4.9 ! 2389.5 1972 5.6
- ~
1973 2524.4 -4.7 1974 2404.7 1.5 1975 2441.6 1.9 1976 2488.7 2.0 1977 2538.8 2559.7 0.8 1978 1.5 2 l 1979 2597.4 . 2574.2 -0.9 1980 1.0 l 1981 2599.3 ; 2662.2 2.4 1 1982 0.3 1983 2670.8 f 2695.3 0.9 1984 1.7 1985 2742.3 l 2735.8 -0.2 1986 . 1.8 i, 1987 2783.7 2848.3 2.3 ' 1988 1.4 1989 2887.8 2932.7 _ 1.6 1990 Compound Annual Growth Rate 1979-1989 = 1.07% t b i 4
I 1 O RESIDENTIAL ENERGY SALES F) . . GIGAWATTH.OUR.S.............. 1
. c .
. . . . . . j C3 . . . . .
=
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O . . . .
- 03. ............%...........E .. ..........J........ .............J. -..........*
N .- -239 7.1979 O a - .
=. . -a . . .
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- : Actual : Forecast , : :
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I 5 1996 4 1968 1972 1976 ., 1980 198L4 1988 1992 YEAR
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e RtSIDeffill. EhtLCY O mstMrTjuN . e AP_Pl I A_MCE , tee tygt,u,1C 1978 ArrLIANCES
\ Ott-LINC ForUI.ATION j RFCO ArrLIANCE
) IN 1972 ESTlHATES SIIRVEY
/\ SAfilRAllUNS g ,
$1514 5 la s_f
-) Fl.211 Ll1T M RIRTHS -
ItOUSEliotD SATURATIoel SATURATIONS 1972 gygggggggg gg.g,g gg 1 BI Nil FURMATIOli TRENDS
} liOUSEllut.D ESTlHA1ES
% TRLND DtVELorED FRON THROUCat im FACM YEAR terront. H0 DEL 1990 l l 9 s -
7 SUBv lV AL , RAir$ y DEATHS _ g)oE 1985 POTE3tilaL ArrLIANCE SHFANT EFFICIE80CY CUIDELINES g p SURVIVAL - ss g RA1ES
-4 \/ INTER 1972 & 1978 I ANIluAL ArrLIANCE
&um LONG BUN
' ' h LNESCT USACE L18tRGY USE SUBSTITUTl001 Itirt uYHENT HICRATION -
GkaMill Ste0RT RUN g gf gp sf f PRICE EIASTICATT / PatrE RESIDENTIAL f ELLC1BBC \ FORECAST ENERGY {] g DEDUCT ENERGY USE OF RA1ES C, C-l & E8 f 00NSIHrTIOld N ALTERNATE h ) / 4 ENERGY C000 SERVAT'ON TECNetotDGY h h %/ TlHE OF ~~~~~~~~~~~3 RESIDLNTIAL USE RATES 7 CONTRIURTlull TO FFAK cp b m , m .e.l ut ,l m - D TR - SEER -..
. RAll.S C.C-1 o,, E oe ReSimmt. IN m-ACmlSTIC. R. 8, Em SIRioGRE mRR RCI Al..
e - . ,, A saturation pattern for each appliance for each year through 1989 is developed from tha NEPOOL model with 1978, the survey year, used as the base year. These saturation patterns are based upon the relationship of household income levels to appliance ownership. A large amount of research was utilized to extract these relationships from the 1970 census information. The saturation patterns used here are based upon data for the state of Massachusetts and can therefore be considered
- reasonable for the Boston Edison territory. These saturations, applied to our 1978 data, regionalizes the saturation to the Boston Edison territory. The resul-cant saturations specific to the territory are shown in Table 2. The forecasted number of appliances is in Table 3. For example, the 1980 electric range saturation is .4633 (Table 2). This means 46% of households in our territory will have elec-tric ranges by 1980. The saturation is multiplied by the number of households in 1980 -- 537,766 -- yielding 249,147 electric ranges (Table 3).
Appliance usage and efficiency are more difficult to determine in view of the Department of Energy's (DOE) yet to be published efficiency goals for new appliances. The previous DOE efficiency goals are no longer in effect. The new goals will be based upon the most efficient and economical appliances that presently exist. Our connaunications with the Department- of Energy and the Association of Home Appliance Manufacturers indicate that there is no agresuent at this time on what the specific requirements will be. Theref ore, this forecast was developed using our best esti-mate of the new standards. Some new efficiency improvements acquired from recent l data
- were obtained for refrigerators / freezers, black and white and color televisions, supplemental heating in the form of wood stoves, and heat pumps with electric backup.
In instances where data on the expected guidelines were not available, the 1979 l efficiency data on appliances achieved through last year's forecast were used. In the previous forecast the assumption was made that DOE appliance ef ficiency goals (these goals are no longer in effect) would be met by 1980: new appliances purchased in 1980 and beyond would meet these goals. By comparing actual 1979 sales versus the expected sales, it became obvious that the efficiency improvements are coming much slower than originally postulated by DOE. For this forecast we have assumed that the efficiency goals for new appliances will be met by 1985. For I
; certain items we were able to obtain data which we feel is representative of the
( most efficient and economical appliances now available. These appliances are refrig-erators, air conditioners, televisions, wood stoves, and heat pumps. For the 1 remaining appliances we have used the efficiency goals in the previous DOE guidelices. I We believe these will be representative cf DOE's position. Assumptions made with respect to usage data are aa_follows:
- 1. Single family home/ apartment split will remain constant throughout -
the forecast. I
- 2. No increase in refrigerator size is assumed.
- 3. Electric heat pumps or electric heat with wood stove backup will replace electric resistance space heat penetration af ter 1980; and af ter 1985, consumers will choose heat pumps over wood stoves due to increased efficiency.
*l. " Refrigerator / Freezers", Consumer Reports, Volume 45, No. 2, February 1980. ,
- 2. Telephone contact from Sally Browne, Director of Consumer Affairs at Electronics Industriec Associated of Washington, D.C.
- 3. Survey of N.E. Fuelwood, Department of Agriculture.
- 4. "An Investigation of Methods to Improve Heat Pump Performance and Reliability in a Northern Climate", Electric Power Research Institute, Project 544-1 EPRI EM-319, January 1977.
l l l
- 4. Hours usage of air conditioners has declined from 485 hours in 1972 to 344 hours.
- 5. Microwave ovans have an inter-appliance substitution effect. This
- means, microwave ovens are estimated to replace the electric consump-r tion of electric ranges at a ratio of three to one; i.e., one kilo-t vatthour of microwave usage replaces three kilowatthours of electric range usane. ,
! f 6. Usage of standard refrigerators is increasing because the size of those refrigerators is increasing. t The next step is to obtain a forecast by application of the energy per house-hold equation. These results are shown in Table 4. The average usage for each year l is multiplied by the number of households in that year yielding the total average 1 t annual consumption for residential households. However, this electric energy per household includes the commercial rates of C, C-1, and K. These master-metered [ rates possess residential characteristics but their energy consumption is reported as commercial. Therefore, their energy must be subtracted from the total energy forecast developed for the residential. Other impacts have to be considered as well. These include the effect of solar water heating, passive solar heating, active solar i heating, electric vehicles and conservation. Table 5 portrays the positive and negative effects of all these impacts except ( for short-run price elasticity. Total acergy consumption for each year is presented
! I first, then the results of each individual impact, followed by the adjusted forecast i ' for each year. Solar water heating is expected to have a saturation by 1989 of -2.75%
for single homes and 2.45% for apartments. We expect .2% of apartments and .5% of single homes to institute passive solar heating by 1989. We also expect .4% of apart-j l ments and .8% of single homes to institute active solar heating by 1989. Electric I vehicles are expected to have an impact of 0.1% by 1989, with a saturation of .004% by 1989. Conservatien effects reduced the forecast by 5,852 MWHS in 1980 and further j by 12,637 MWH by 1989. The fo' recast numbers in Table 5 do not contain impacts of price. This impact j .is measured through short-run price elasticity. Price elasticity measures a con-i sumer's response to a price change. Table 6 sh'ows the short-run effects of the price i changes in each year. Territory specific studies have shown the short-run elasticity i < to be approximately -0.2%. For example, from 1981 to 1982, the price of electricity increases by 2.35%. This will cause a decrease in electricity consumption by 0.4%, ' 4 all other things being equal. Then, 0.9953 (which is 1 minus .0047), is multiplied , by the adjusted forecast results in Table 5. This calculation yields a decrease of 12,275 megawatthours. This reduction (or increase as the case may be) affects every year of the forecast and is shown in Table 7. For exampJe, the 4.59% decrease in i price in 1982 will stimulate an increase of 26,626 megawatthours in 1980 and all l succeeding years. The bottom line of Table 8 represents the complete impact of short-l run elasticity on the residential class's total energy consumption for a ten-year period. Long run elasticities have been calculated for the residential sector. However, t they have only been utilized to reassure the reasonableness of the assumption that the potential effects of long run elasticity are already fully contained in the residential forecast through the effect of appliance efficiencias. For example, the 1 final forecast number developed for 19P using appliance efficiencies was 2888 GWH,
' whereas applying long run elasticity the ssulting forecast figure is 3,995 GWH for i
1989 - a dif ference of 35%. Long run price elasticity effects are the result of consumers relacing existing appliances. The effect of price along eould cause the consumption Icvel of 3995 JWH. The mandated appliance efficiencies will cause a consumption of 2888 GWH. Constant price and no mandated efficiencies would cause a 4 consumption of 7992 GWH. The mandated reduction is so large that there are no price included changes. I j j ~ l
e e 's .e Appliance Assumptions Electric Range - I The saturation of ranges is expected to increase from 46% in 1979 to 53% by 1989. l Usage for new ranges will decline from an average use of 1191 kWH in 1979 to 1174 kWH in 1985, and remain constant thereafter. Ranges have an expected life of 12 years. l 1 The average annual usage per household for ranges is expected to increase from 348 r kWH in 1979 to 504 kWH in 1989. Therefore, the total energy consumed (average usage per household times number of households) by ranges in 1979 was 184 GWH. This will rise to 302 GWH by 1989. This increase is because the growth in electric ranges is occurring faster then the growth in households. In addition, the average annual con-i sumption per household is reduced due to the impact of microwave ovena. For example, I the 1989 consumption cited above (504 kWH) will be further reduced by 78 kWH.
- Refrigerator -
Frost-free We have used 1248 kWH per year by 1985 as an estimate of the new DOE guidelines. This information is from the February 1980 issue of Consumer Reports. We have assumed no change in size over the forecast period. This is in good agreement with the estimate of local distributors of General Electric and Whirlpool. These distri-
. butors report that the 17 to 21 cubic foot models are the most popular sizes purchased.
l Refrigerators have an expected life of 15 years. Therefore, we expect that by the year 2000, consumers will own or purchase only the most efficient models. The saturation of frost-free refrigerators is expected to increase from 54% in l' 1979 to 62% by 1989. The average annual use per household for frost-free refrigerators is expected to decline from 1166 kWH in 1979 to 1004 kWH in 1989; and usage for new refrigerators will decline from 1516 kWH in 1979 to 1248 kWH in 1989. The total energy consumed by refrigerators in 1979 was 618 GWH. This is expected to decline in 1989 to 602 GWH.. This decline reinforces the fact that efficiencies will be occurring in refrigerators even with increasing number of households. I t, Standard
, The saturation of standard refrigerators is expected to decline from 57% in 1979 ' to 42% in 1989. Standard refzigerator usage is expected to increase from 778 kWH in 1979 to 821 kWH in 1989. This is due to an increase in the size of the refrigerators.
With saturation declining by 3% and usage increasing slightly (0.5%) over the forecast period, we can expect average usage per household and total energy consumption to de-t cline. Average usage per household will decline from 837 kWH in 1979 to 635 kWH in 1989. Total energy consumption will decline from 470 GWH in 1979 to 381 GWH in 1989. F Freezers - The usage for freezers has been ratioed in agreement with the Company's satura-tion survey - 4.1% of households have frost-free freezers, and 14.03% have standard freerers. We have assumed that frost-free freezers will increase their saturation from 4% in 1979 to 7% in 1989, while standard freezers will decrease - from 14% in l 1979 to 12% in 1989. Freezers have an expected life of 17 years. Usage for new l freezers, frost-free and standard, is declining slightly (both by 1%), over the ;
' forecast period. Usage per household is increasing from 75 kWH in 1979 to 91 kWH l by 1989 for frost-free, and decreasing for standard models, from 165 kk" in 1979 to 146 kWH by 1989. Total consumption for both frost-free and standard freezers l is expected to increase; frost-free from 40 GWH in 1979 to 55 GWH in 1989, and standard freezers increasing slightly from 87 GWH in 1979 to 88 GWH in 1989.
e .*, p k Dishwashers - The' saturation f or dishwashers is also expected to increase - from 44% in 1979 I to 60% in 1989. Usage for new dishwashers in 1985 will be 336 kWH; this is down l from 349 kWH in 1979. Average annual usage per household will increase from 156 kWH in*1979 to 193 kWH in 1989, with total consumption increasing from 83 GWH in 1979 l to 116 GWH in 1989. Dishwashers have an average life of 10 years. )
- Washers -
F Saturation of clothes washers over the next 10 years is expected to remain j l constant at an average of 72%. These appliances have an average life expectancy of i 10 years. Usage fer new washers is expected to be more efficient dropping from 91 kWH in 1979 to 80 kWH in 1985 and held constant thereaf ter. The average annual use per household for washers will drop from 74 kWH in 1979 to 67 kWH in 1989. Total consumption will increase slightly from 39 GWR in 1979 to 40 GWH in 1989. Dryers - The saturation of dryers is expected to incresse slightly from 31% in 1979 to 34% in 1989. The average expected life of a dryer is 13 years. Usage for new dryers is expected to be 958 kWH annually by 1985 and held constant thereaf ter. This
). is down from 974 kWH in 1979. The average use per household for dryers is expected to be on the rise from 313 kWH in 1979 to 330 kWH in 1989, with total energy consump-j tion rising from 166 GWH in 1979 to 198 GWH in 1989.
Water Hester - Water heat satt. ration rates are expected to grow over the forecast period from i 13% in 1979 to 17% in 1989. Water heaters have a life expectancy of 20 years. New usage for water heaters is expected to be 4172 kWH by 1985 and remain so thereaf ter; { this is a decline from 4463 kWH in 1979. Average use per househeld will increase J 'from 603 kWH in 1979 to 711 kWH in 1989. Therefore, total consumption is also expected to grow - from 320 GWH in 1979 to 426 GWH in 1989. Microwave Ovens - The saturation of microwave ovens will grow quite fast from 4% in 1979 to 17% in 1989 or at a compound annual growth rate for the 10-year period at 15%. Micro-vave ovens have an expected life of 10 years. Usage for new microwaves is becosing slightly more efficient at 182 kWH annually. We expect microwave ovens to reach this efficiency by 1985. This usage is down from 186 kWH in 1979. Average usage j per household ranges from 7 kW in 1979 to 26 kWH in 1989. Therefore, total consump-4 tion can be expected to increase from 4 GWH in 1979 to 16 GWH in 1989. Televisions - Color Color televisions have a saturation in 1979 of 73%. In 1989 the saturation level i is expected to increase to 89%. Color televisions have an expected average life of '. six years. According to data from the Electronics Industry Association, color tele-visions have already achieved their optimum efficiency at 198 kWH. This figure is , held constant throughout the forecast period. The average use per household for these TV's is dropping from 225 kWH in 1979 to 202 kWH in 1989. At the same time total consumption will increase from 119 GWH in 1979 to 121 GWH in 1989.
' e d _ . . . _ ._
Black & White Saturation levels for black and white TV's will steadily decline from 68% in '_. 1979 to 34% in 1989. Black and white televisions can expect to have a life of 3 years. New sets have an assumed usage of 100 kWH, and this figure is held constant for the forecast period. Usage per household for black and white sets is declining from 68 kWH in 1979 to 60 kWH in 1989. Total consumption will decline from 36 GWH in 1979 to 30 GWH in 1989. Air Conditioners - Room The saturation level for room air conditioners will increase. In 1979 the ( saturation is 44% and in 1989 it rises to 61%. The expected average life of this appliance is 12 years. We expect room air conditioners to have a usage of 296 kWH by 1985. This is due to increased efficiency. Average usage per household is assumed to grow from 252 kWH in 1979 to 238 kWH in 1989. Total energy consumption for 1979 is 134 GWH increasing to 142 GWH by 1989. s Central While room air conditioners vill increase over the forecast period at a compound 4 annual growth rate of 4.5%, central air conditioning vill increase by 3.8% per year. The saturation level is expected to grow from 5% to 6%. Central air conditioning {' can expect an average life of about 20 years. New air conditioners coming on line are expected to have a usage of 699 kWH by 1985 and held constant thereaf ter. Average use per household is expected to remain constant at 60 kWH annually for the forecast-ing period. Total energy consumption of 32 GWE in 1979 will increase, because of growth in households, to 35 GWH in 1989. Electric Sp' ace Heating - I t Penetration refers to the proportion of new households who will install electrit resistance heat. Information from our Residential Department indicate that the penetration rate will approximate 20%. As a result, the saturation for electric heat in homes and apartments is expected to increase from 6% in 1979 to 10% in 1989. When determining usage data, home heating and apartment heating are split according to our most recent estimates: home 28% and apartments 72%. Electric ( space heating has an expected average life of 20 years.__New usage for apartment heating will drop from 5615 kWH in 1979 to 2362 kEH in 1989. For home heating, it is expected that wood stoves, for supplemental heating, are presently entering into I consumer's preferences, reducing the heating usage from 15,218 kWH in 1979 to 9740 kWH by 1985. From 1985 to 1989, the heat pump with electric resistance heat backup will be the consumers' choice over the supplemental wood stove. The heat pump is expected to become much more efficient by the mid-eighties. The usage for electric heating is expected to drop down to 6948 kWH annually by 1989. . Average usage per household will show an increasing trend in kilowatthours due i to sxpected growth in households which have electric heat. We expect home heating ' to increase from 337 kWH in 1979 to 433 kWH by 1989, while apartment heating is expected to increase from 321 kWH in 1979 to 392 kWH in 1989. Total consumption for home heating use per household and apartment heating per household is expected to grow from 348 GWH in 1979 to 494 GWH by 1989. i Miscellaneous and Lighting - l The average usage per household, developed in Table 9, was compared against actual
I e e% c, .. _ _ _ . The result usage figured for 1978 to determine data for miscellaneous and lighting. is a constant number of 421 kWE. t Table 8 shows the expected average life of each appliance. Table 9 shows the average usage per household for each appliance for all of the forecast year. These tables together with the number of households in the demographic ?ection provide the input for growth in total consugtion for each appliance found 1. Table 10. 1 l q- , I I i ( s k o l f s t l
, I i
l
, n l l i
i l l l l 1
- - -- - .- __ - - - . . ~ _ . . . .
O i* j .* 4 e Table 2 SECO Appliance Saturation Forecast 1979-1990 . 1978* 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Range 45.53 45.92 46.33 47.15 47.96 48.78 49.56 50.32 51.04 51.71 52.33 52.91 $3.46 Refrigerator, FF 52.63 53.78 54.9) 55.81 56.70 57.59 58.48 59.36 60.07 60.78 61.49 62.20 62.90 ; Refrigerator STD 59.13 56.94 54.75 53.29 51.83 50.37 48.91 47.45 45.99 44.53 43.07 41.61 40.15 , Faeezer FF 4.01 4.22 4.41 4.68 4.96 5.24 5.52 5.82 6.08 6.35 6.62 6.90 7.17 Freezer. STD 14.03 13.73 13.33 13.20 13.05 12.92 12.77 12.63 g2.52 12.60 12.28 12.15 12.03
- Dishwasher 42.25 43.51 44.59 46.54 48.46 5 0. 36 52.08 53.91 55.54 57.02 58.39 59.62 60.80 Washer 71.65 71.60 71.46 71.62 71.76 71.92 72.87 72.24 72.40 72.54 72.72 72.88 71.96 l Dryer 31.37 31.25 30.99 31.23 31.47 31.72 31.97 32.23 32.49 32.76 33.02 33.27 33.51 Water Hester 12.38 12.63 13.0% 13.58 14.11 14.66 15.18 15.69 16.14 16.58 16.97 17.34 17.68 Microwave 3.57 4. 36 5.2{ 6.14 7.11 8.14 9.23 10.38 11.57 12.83 14.14 15.51 16.92 TV Color 70.94 72.64 74.34 75.82 77.30 78.79 80.28 81.77 83.26 84.74 86.23 87.72 89.20 TV 8/W 70.38 6 7. 56 63.60 60.63 62.74 54.70 51.73 48.76 45.79 42.82 39.8 5 36.88 11.91 Boom A/C 42.46 43.62 4 4. 39 46.43 48.42 50. 39 52.30 54.14 55.82 57.37 58.80 60,12 68.35 central A/C 4.78 4.81 4.78 4.91 5.G4 5.20 5.33 5.49 5.68 5.84 5.99 6.18 6.34 Heating 5.21 5.53 5.95 6.50 7.05 - 7.61 0.14 8.66 9.14 9.58 9.99 10.37 10.73 cActual esturations f rom Company sponsored appliance survey.
_ 54 -
- - - - - _ . _ ~ - _ - _ _ _ -
~
~~ -- - - __ _
1 . 1 8
. 9 t l Table 3 8ECo Appliance Number 1979-1990_ '
1988 1989 1990 1985 1986 1987 1982 1983 1984 1979 1980 1981 110604 317248 32388) 289140 296602 301727 265416 273528 283420 364973 372951 180992 243448 249147 257118 143202 149077 357002 Range 181785 322930 332071 255642 249494 243193 285118 295395 304601 272141 2672 % 261555 41429 8efrigerecor, FF 28681) 282444 277729 1929) 41172 294427 290849 33451 35332 37298 8efrigerator STu M1871 27449 2918) 11345 72886 72851 72867 2217) 23715 2554) 72513 72597 727 % 72814
% 8272 Freezer, FF 78684 72044 72220 72447 322752 334987 34 573 357482 72791 282388 296297 M9h '5 4 M988 415068 Freezer, M D 239790 254008 268881 420729 42619) 411629 230673 401281 409240 4852 s 199487 203095 Dishwasher 384288 190898 197128 188805 192421 195990 379592 177866 181517 385258 101971 107090 Washer 366654 170449 175159 93792 97385 100725 16%74 :t2204 36198 90186 92998 102486 Dryer 70125 14118 78086 67215 75159 83928 66959 45444 52488 59664 525969 540291 Water Heater 23115 280/8 31518 19148 470015 483838 497735 511817 427787 441806 455860 2 % 529 22tl32 205396 Hierawave Owen 385306 399795 413814 280273 24091 251511 TV, Color 347288 106724 293742 349007 % 0480 37160) 358174 142019 330909 311197 174380 3%972 18402 TV, 8/W 267962 2825 % 296979 35554 17055 231254 238784 251408 11557 11007 14 M2 soom A/C 27892 29858 M266 25501 25705 26798 Central A/C 14871 14733 15052 l i t.!! 1167% 14025 12121 1251) 12v11 35478 16158 37229 10821 18247 1869e 12778 3 % 88 14588 lleating - thine 29694 10751 18775 16349 27445 28600 Apartment
e s% .. I f I Table 4 l l Calculation of Preliminary Forecast without Adjustments Number of Total Energy Aversge BECo Households _ Consumption (kWH) Use 1979 5,427 530,157 5,423 537,766 2,916,305,018 1980 1981 5,4 8 545 785 , 9{,01 2 568 l 1 ' 8, 1,148 3, 56 837 ,
!!ll4 i: !!!:!!! !!!!!!!!!!!!!
1;'; i:! I'5:'!? ;;g6:$5;;il: 1;'; :i'; l'i:'t 3.256.902.67o t i i { i i
. _ .- _ _ . - . . - _ _ _ , _. _, - _~ , - _-
Table 5 Adjustments
- to Forecast: 1980-1990 ,
Minus Minus Plus Plus Total Ener8y Minus Solar Whter Passive Solar Active Solar Electric Minus Forecast Ti Year Consumption C, C-1 + K Heatins** Heatina** Heatina** Vehicles ** Conservation ** After Adjustment 1980 2,916,305,018 283,000,000 0 0 0 304,000 5,852,000 2,627,757,000 1981 2,957,063,130 283,000,000 469,000 38,000 112,000 554,000 9,005,000 2,665,218,000 1982 2,996,172.568 283,000,000 938,000 76,000 225,200 909,000 9,459,000 2,703,834,000 1983 3,833,037,251 283,000,000 ,1,406,000 115,000 337,800 1,266,000 9,913,000 2,740,207,000 1984 3,068,591,148 283,000,000 1,875,000 153,000 450,000 1,589,000 10,367,000 2,775,236,000 1985 3,103,925,400 283,000,000 2,343,000 191,000 563,000 1,824,000 10,821,000 2,809,957,000 1986 3,135,126,215 283,000,000 3,066,000 273,000 599,000 4,440,000 11,275,000 2,842,551,000 1987 3,166,495,497 283,000,000 3,789,000 356,000 635,000 7,866,000 11,728,000 2,876,116,000 1988 3,196,854,914 283,000,000 4,511,000 438,000 672,000 13,140,000 12,183,000 2,910,535,000 1989 3,226,770,460 283,000,000 5,23k,000 521,000 708,000 21,040,000 12,637,000 2,947,126,000 1990 3,256,902,670 283,000,000 5,957,000 603,000 744,000 37,096,000 13,091,000 2,992,092,000
*All Numbers Represent KWhs. ** Alternate Energy and Conservation Projects Performed Within The Company.
_ 57 -
i
. . *, c.
I l l T l l
/
Table 6 Development of Short Run Elasticities
- Price P a P g
eg SRE g g 1979 .0541 1980 .0596 +.1020 +.2 +.0125 .9796 1981 .0610 +.0235 +.2 +.0047 .9953 g 1982 .0582 .0459 +.2 .0092 1.0092 1983 .06 12 +.0515 +.2 +.0103 .9897 1984 .0624 +.0196 +.2 +.0039 .9961 1985 .0610 .0224 +.2 .0045 1.0045 1986 .0653 +.0705 +.2 +.0141 .9859 1987 .0636 .0260 +.2 .0052 1.0052 l
. 1988 .0602 .0535 +.2 .0107 1.0107 , 1989 .0599 .0050 +.2 .0010 1.0010 1990 .0599 .0050 +.2 +.0010 1.0010
- Formula: 1 - (Pg
- e )t= SRE Where: SRE = Short Run Elasticity i
P =P g - Pt,7 t g. t-1 e = Year e = Elasticity in year t (source is further described in separate document) o _ . . , ~ _ . , , s t . a e
.7 f
Table 7 lepect of Short Sun Price Elasticity on Energy Consumption 1980 to 1990 1987 1983 1984 1985 1986 1987 1988 1989 1990 1980 1981 2,627,757 2,665,218 2.703,834 2,740,207 2.775,236 2,809,957 2,842,551 2.876,116 2,910.535 2,947,126 2,992,092 Model Forecast (HWh) ,
.9796 1979 Elsaticity 2.574.151 2,756,351 2.788,945 2,822,510 2,856,929 2.993.520 2.938,485 Difference -53,606 2,611,611 2,650,228 2.686,601 2.721,629
.9953 1980 Elsaticity 2,599,337 2,637,953 2,674,326 2,709,355 2,744,077 2.776,670 2,810,236 2,844,654 2.881.246 2,926,211 Di f ference -12,275 1.0092 1981 Elseticity 2.662,222 2.698,560 2,733,624 2,768,346 2,800.940 2,834,505 2,968.923 2,905,515 2.950.480 Difference 424,269
.9897 1982 Elasticity 2,670,800 2,705,828 2,740,502 2,773,144 2,806.709 2.841,128 2.877,720 2.922,684 Di f f e renc e -27,761 2,695,276 2,729,997 2,762,591 2,796,156 2,830,575 2.867,167 2,912,132
.*961 1983 Eleaticity Difference -10.553
' 2,742,282 2,774,876 2.808,442 2,842,860 2,879,452 2,924,417 l.0045 1984 Elastscity Difference +12.285 2,735,751 2.769,316 2,803,734 2,840,326 2.885,291
.9859 1985 Elasticity Di f f erence -19.125 l 2,783,736 2,818,135 2,854,726 2,899,691 1.0052 1986 Elseticity
+14,400 Dif f erence 2,848,289 2,884,880 2,929.845 1.0107 1987 Elasticity
+)0,154 Dieterence 2,887,765 2,932,7)0 1.0010 1988 Elasticity 42,885 Difference 2,935,663 1.0010 1989 Elsettetty + 2.9 3 3 plif erence 2.599,337 2,662,222 2,6 70,800 2,695,276 2.742,282 2.735,751 2.783,716 2,868,289 2.587.765 2.935.663 Actual Forecast 2,574,151
s% .* l
~
\
l I l PRIS1-m-15 TABLE 8 AVERAGE LIFE OF APPLIANCES s I^ RANGE 12 j i REFRIGERATOR 15 FREEZER 17 DISHWASHER 10 WASHER 10 DRYER 13 t WATER HEATER 20 MICROWAVE OVEN 10 I T.V., COLOR 6 T.V., BLACK & WHITE 8 ROOM A/C 12 f 20 CEiTRAL A/C ELECTRIC HEAT 20 4 Source: Woburn Times, December 14, 1978 f t.
Table 9 Average Use Per Household 1978 to 1990 (Includes Rates C, C-1 and K) , Appliances 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Ran8e 332 348 363 379 395 410 426 442 457 478 489 504 520 Refrigerators, FF 1,184 1,166 1,147 1,131 1,112 1,095 1,075 1,058 1,039 1,022 1,004 986 968 Refrigerators, Std 887 862 837 811 786 761 735 711 685 660 635 609 583 Freezer, FF 73 75 76 78 79 81 83 84 86 87 89 91 92 Freezer, Std 167 165 163 161 159 157 155 153 151 149 147 146 144 Dishwasher 153 156 160 164 167 171 175 178 182 185 189 193 196 Washer 74 73 73 72 71 71 70 69 69 48 67 67 66 Dryer 311 313 315 316 318 320 322 323 325 317 329 330 332 Water Heater 592 603 614 624 635 645 657 669 679 690 700 711 722 Nicrowave 7 9 10 12 14 16 17 19 21 23 24 26 28 TV, Color 227 225 222 220 218 216 213 211 209 207 204 202 200 TV, B/W 70 68 67 65 62 60 59 57 55 54 52 50 49 Room A/C 253 252 251 249 248 247 246 244 243 241 240 238 237 60 60 60 60 60 60 60 60 60 60 60 60 Central A/C 61 Heating,I!ome 327 337 346 356 366 376 385 394 404 414 423 433 442 Heating, Apartment 314 321 328 335 342 349 356 364 371 378 385 392 399 Hiscellaneous & Lighting 421 421 421 421 421 421 421 421 421 421 421 421 421 Total 5,453 5,454 5,453 5,454 5,455 5,457 5,455 5,457 5,457 5,460 5,458 5,457 5,461
- i.ess Microwave Adjustment * -21 -27 -30 -36 -42 -48 -51 -57 -62 -69 -72 -78 -84 Average Use 5,432 5,427 5,423 5,418 5,413 5,403 5,404 5,400 5,395 5,391 5,386 5,381 5,377
*The use of electric ranges is reduced by three times the annual use of microwaves to reflect the reduction in use of the range as a result of the introduction of the microwave.
i
, Table 10 Growth *in Energy Consumption by Appliance 1979 to 1989 r '*
Appliance 1979 1989 % Growth t . I l [ Range 184 302 5.1 Refrigerator FF 618 602 -0.3 i Refrigerator STD 470 381 -2.1 -l f Freezer, FF 40 55 8 3.2 i Freezer, STD 87 88 'O.01 l , t , Dishwasher 83 116 3.4 l 1 i Washer 39 40 0.22 i
< {
Dryer 166 198 1.8 Water Heater 320 426 3.0
. Microwave 4 16 15.4 j TV, Color 119 121 0.2 l TV, Black / White 36 30 -1.8 Room Air Conditioner 134 142 0.7 i
Central Air Conditioner 32 35 1.2 ) ( { Electric Space Heat 349 435 4.0 I l r t. f
*all in gigtwatthours i i s
. .s ..
k o 9 RESIDENTIAL: ELASTICITY EFFECT o . .G.IGAWATT.liotMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o.................................. . . .
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- Unadjusted; o )
l . . o. o . .
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. Model :
. Adjusted f6r Short-Run .
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h Ip., t 1 l e
# G i
I a 6 O COMMERCIAL f I_ n.
===
m
o .*. .. l CorefERCIAL FORECAST Summa ry i The Commercial Sector Forecast is developed through a single equation eco-nometric model. The assumption underlying this model is that the demand for l electric energy in the Comunercial sector is dependent upon the level of ecenon- ) ic activity. The current methodology is reasonable, used the best information 1 available to us and is statistically sound. l The hypothesis is that the electric energy consumption is related to three
' basic factors: economic activity within the Company's service area; economic activity outside the Company's territory (e.g. hospitals, finance, insurance, ;- etc., provide export services to a larger area); and the usage will also be re-lated to price.
The final variables selected were Gross State Product, the number of house-holds in the service area; the number of commercial customers in the service area; and the real price of electricity. The forecast has been modified by the effects of mandate.; conservation, cogeneration, alternate energy, new technology and short and long run price elasticity. i I The following pages present a flow chart and the results of the Commercial j Sector Forecast. I 1
, i 1
i l l i
a .s o,
. }? , =
Commercial Class Energy Forecast ! (Gigawatthours) l Year Actual Forecast Growth 1970 2894 9.5 1971 3136 8.4 1972 3346 6.7 (' 1973 3756 12.2 1' 1974 3691 -1.7 1975 3924 6.3 1976 4144 5.6 1977 4277 3.2 1978 4428 3.5 _ 1979 4550 2.8 1980 , 4633 1.8 1981 4772 3.0 1982 4978 4.3 1983 5169 3.8 1984 s 5335 __ 3.2 P 1985 5488 2.9 1986 5629 2.6 1987 5737 1.9 1988 5857 2.1 1989 5964 1.8 6. 1990 6128 2.8 6 Equivalent compound growth rate 1979-1989 2.7% i l
- ~~ -. -- ~ . . . -_
= i e ,
OltRtERCIAL ENCCT FCIECAST
/
TilEORETICAL RASIS FIS Pt)DE L N/ . VARIARLE
.SEIICTION TINE OF
\/ ALTERNATE NRG
(( RECRESSION s FORECAST OF . s ,
/ g
' GROSS STATC STUDY g g FRODUCT
~
l COGENERATION l CONSERVATION l g g b \/ h b Q sp FRICE FORECAST CotMERCI AL ComERCIAL STATISTICAL I IIINI TilEORETICAL
* \
F ) ) /
# # y[gg SEl.ECTION ELASTICITT 0F EQUATION ^
t T ADD ENERCY 1DNC RUN USE OF RATES FRICE C. C-L AND g e EIASTICITT
% US HO W )
(DEMOCRAPHIC)
' nim TECHN01DCT FORECAST OF g NUNRER OF \
/ CapetERCIAL /
CUSTONERS
- RATES C, C-1 AND E ARE HDDELLED IN RESIDENTIAL, BUT ARE CotetERCIAL RATES AND HUST RE ADDED IN.
. .s ..
o COMMERCIAL CLASS CONSUMPTION
=r.................................. . . . G I. G. A. W. A. T. IH. O. . . .U.
. ..R.S.
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Introduction i Because of the diversity of customers both in size and function, the energy
, sales in the commercial sector are more difficult to forecast than either the
- residential or industrial sectors. There are airports, office buildings,
- schools, shopping centers, banks and large warehouse facilities. Included also in this group are the classic family-owned retail stores and small service , ; I oriented businesses (insurance and financial service). In addition, the present
{ unavailability of certain key data pertaining to the class characteristics of , i energy consumption poses more restriction to a detailed analys.is. There is not I j , a satisfactory measure of overall output for the commercial sector. End-use
- , modeling is not yet within our reach because indicators such as square footage l L of office space are not available on a historical basis. In addition, the area i served by Boston Edison Company does not fit county lines so that there are i e further problems in the collection of territory specific data.
, I l
Approach and Methodology i l To forecast energy consumption, factors that will influence the energy con-i sumption patterns such as the cost and the availability of alternative forms of i energy supply, the environmental structure, the life style, the level and compo-l : sition of economic activity should be considered as explanatory variables in the [- model. Some of these factors can be quantified, others are more difficult to measure, consequently, the actual specification is dependent upon expert pro-fessional abilities and intimate knowledge of the BEco. territory. In order to j f. utilize all available variables explicitly and sufficiently in the building of the BECo. commercial energy forecasting model, it is believed that the develop-ment of*an econometric model is most suitable. An Econometric Model can be used j to capture the structural shifts that will occur du2 to a change of an input and j study the impacts of such a change. The structural and final form of the model is established through the Statistical Package for the Social Sciences (SPSS). I In particular, we use the stepwise multiple regression analysis through which l l } different forms of equations esa be experimented with to verify the existence
- 1. of a relationship between sales and relevant factors, test their appropriate-ness, and test their significance so that the most appropriate form can be j chosen.
~
The multiple regression analysis calculates historical trends in the re-lationship between electric energy consumption and various economic variables and uses them as forecasting relationships to project future electric energy consumption. l There are four (4) general steps discussed herein with respect to the de-velopment of the econometric model: [ Determination of the variables that theoretically impact commercial i l 1. ;
- , energy consumption, i i
- 2. Determination of the general form of the equation,
- 3. Definitions and evaluation of statistical measures through which to determine best model fit, and
- 4. Analysis of the results and actual equation choice.
. .s ..
~
Each of these are discussed in detail. 1 I
'. Determination of variables that theoretically impact commercial energy ,- consumption.
Commercisl Customers CUST T Residential Households RHH ( Population-BECo. Service Area POP j I People per Household PPH There are four demographic variables which influence'the economic activity in an area. Commercial customers are the number of actual customers, i.e., if a customer is billed on two rates the commercial customer count would include it only once. The C, C1 and K Rates have characteristics of residential custom-ers so these rates have been deducted from commercial customer counts. Residen-tial households are the number of households in the residential sector. Details
! are available in the residential energy forecast. Population by County of Mas-sachusetts is available from 1960 to 1978 in Current Population Reports issued
' " by the Census Bureau, where 1960, 1970 and 1975 are the census years and the remainder are the estimates between the census years. However, the BEco. ser-vice territory does not coincide with the county lines: BECo. population makes up 48% of Middlesex County, 40% of Norfolk County and 90% of Suffolk County. Therefore, in order to obtain population for the BEco. service area, additional ( calculations were done. First, population of the cities and towns served by BECo. we're taken for the years 1960, 1970, 1973, 1975 and 1976 from Current Population Report. Then, based on the trend of county population, the BECo. j service area population within each county was estimated for the years between 1 1960 and 1970, 1970 and 1978. Regression analysis was used to calculate the i estimates. It appears to be a reasonable method to apply. After population and residential households are determined, people per household is simply the , division of population and residential households; i.e., PPH = POP - RHH. ) We expect to observe positive signs on these variables. In other words, { an increase in these four factors will lead to more electricity consumption. g-On the other hand, historical dats indicates that in our service area, popula-tion has a tendency to decline while sales continue to increase. Therefore, a negative sign for POP and PPH is not surprising for the BECo. service territory. Real Farsonal Income RPI Real Personal Disposable Income RPDI Per Capita Income of Mass. PCIM l Total Personal Income of Kass. TPIM Electricity is a norral good. By the economic definition, a normal good is one whose consumption varies directly with money income at a specific set of constant prices for all levels of money income. As such, electricity con-sumption is expected to vary directly with changes of income. Data for real personal income and real personal disposable income are collected from the quar-terly data bank for the Boston Edison Economic-Electricity Consumption Forecast-ing Model prepared by Wharton Econometric Forecasting Associates. In their def-inition, the RECo. service territory is the sum of three counties - Middlesex, i Norfolk and Suffolk. Both per capita income and totsi personal income for Mas-sachusetts were published in the Survey of Current Business, and deflated by the Consumer Price Index of Boston, Massachusetts. Average Real Psice of Electricity TYP3 r Average Real Gas Price GAS Lagged Average Real Price of Electricity LTYPB Negative signs are expected on price of electricity and lagged price of electricity. This is the law of demand. However, a positive sign should ap-pear on the co-efficient of gas price in view of the fact that a substitution effect exists between gas price and electricity consumption. In other words, when the price of gas increases, consumers will consider substitution of elec-tricity for gas in order to attain maximum satisfaction from their disposable income, hence, consumption in electricity increases. Gas and electricity are competitive to consumers. This is the Substitution Effect in Economics, i.e., it is the change in quantity demanded resulting from a change in relative price while holding real income constant. The price of oil was left out because we could not obtain satisfactory data. The BECo. electricity price used was adopted from Typical Electrical Bills published by the Federal Power Commission. The 12 kW/1500 k:iH level was chosen because the majority of commercial customers fall into the G1 and G2 rate cate-gories and the average demand of these rates is between 10 kW and 20 kW. There- [ ( fore, it is felt that the typical electrical bill at 12 kW/1500 kWH represents the average price in the commercial sector. The average gas price was the com-mercial non-heating gas price charged by Boston Gas Company. It is assumed that electricity and gas are more competitive for non-heating purposes in commercial establishments. Both prices were calculated in real terms, deflated by the Bos-ton Producer Price Index. { An alternative of the price variable was tested,. based on the assumption that the response of demand to changes in price is likely to be in the nature , of a lagged effect. The choice between average and marginal prices has been considered. In economic theory, individuals base the decision on marginal values. In real life, most consumers are generally aware of their total electric bill and of the total quantities consumed. As such, average price appears to be preferred in the model. At the pre'sent time, marginal price for the comrercial sector is not available for comparison due to the fact that rate reclassification took place in 1974, and any previous information is not consistent for forecasting purposes . The Consumer Price Index and Producer Price Index are issued by Bu-reau of Labor Statistics - Producer P-ices and Prices Indexes. See Table I. Non-manufacturing Employment BNE
. .s ,. .
l l 1 Employment is an important economic indicator. Promoting maximum employ-ment is one of the means through which to improve the economy's performance. We expect the sign on this variable to be positive. Data for BECo. non-manu-facturing employment was obtained by totaling non-manufacturing employment of l the cities and towns served by Boston Edison Company, which is available at the 1 ( Division of Employment Security, Commonwealth of Massachusetts.
, Gross State Product of Mass. GSP Gross National Product GNP Both are primary measures of economic growth. State estimates of gross product, by itself and in conjunction with other economic data, is a useful and informative indicator of state economic activity. Defined as "The aggregate earnings of labor and property ... less the intermediate products purchased",
it can be used to measure economic growth over a period of time, and provides a basis for comparing the economic performance in one state (or region) with that in another. Gross State Product is computed using several methods employed in estimating gross national product, and is the sum of the pri products plus the farm and government gross product figures.yate non-farm gross In Massachusetts, many of the major economic events take place in the area served by BECo., and
, it seems appropriate to include gross state product as an economic indicator.
Data for gross state product was available through 1977 from the Federal Reserve Bank. In order to meet the computational need in processing regression analysis, 1978 gross state product was estimated by assuming 10% growth over 1977. New England Economic Project published the 1978 growth rates for real personal. income and esployment of Massachusetts as 3.8% and 4.3% respectively. 6.1% was the deflation rate in 1978. As a result, 10% growth appears reasonable
! for 1978 gross state product. The producer price index was applied to trans- ! form gross state product into real terms.
Heating Degree Days HDD Cooling Degree Days CDD These are the 2 variables that reflect the weather sensitivity of BEco. commercial energy sales. Positive signs should appest on both variables. These data are available in the Local Climatological Data sheets published by the National Oceanic and Atmospheric Administration. I Dummy Variable DY The dummy variable is so constructed as to represent certain factors that
- are not naturally quantifiable. It takes only 2 values, O and 1. BECo. his-torical sales data indicates that a downward shift occurred in 1974. This vari-able was tested to identify a conservation response and/or structural variation in energy sales after 1973. The values are set to O from 1960 to 1973, and 1 from 1974 to 1978.
The source of data, the historical base period of the data, and the type of forecasting relationship are shown in Table 2. I J. S. Connolly, Gross State Product in the New England States, 1975-1976, Federal Reserve Bank of Boston
. .s ..
Table 3 presents annual data for each of these above variables for the period 1960 through 1978.
- 2. Form of the Equation t-( The BEco. energy forecast model can be expressed in a single linear equation assuming that the depen.ftut variable SALE is a linear function of a series of independent variables.
7 I i i The general forr can be written as: j l
=
i, Y B0+BXg7+B2 2 +****** n n Y = BECo. commercial energy sales (excluding
$ sales of C, C-1 and K)
( X ,......,X, = eccnomic and demographic variables 3 B = c astant ters or intercept j 0
' B g ,......,B, = coefficients of the independent variables The final form will be determined by the results of the multiple re-gression analysis.
- 3. Definition and Evaluation of Statistical Measures The least square method was used to estimate the mathematical fore-casting relationships and to obtain several statistics with which to test
. the significance of the results. The statistical criteria we are using to test the significance of each independent variable and the equation are indicated below:
2 R_ - A measure of the " goodness of fit" of the regression line. It measures the proportion of the variation in the dependent variable which is " explained" by the regression equation. Its values range from a mini- { mun of 0 to a maximum of 1.0. t Overall F - It is an overall test of significance for " goodness of fit" of the regression equation.
' Individual F - Significance test of the regression coefficients of the equation. The t value can be transformed by taking the square root of the individual F, with the appropriate sign.
D.W. (Durbin Watson) - It is used to examine the existence of serial correlation of the error term. , l
- 4. Analysis of the Results In this year's model construction, the parameters in the stepwise l procedures were so designed that only those variables whose estimated co- (
efficients are statistically significant and where the correlation between independent variables does not exceed 60%, will be selected. As a con-sequence, the problem of multicollinearity is avoided. 1 I
! , j All the relevant factors initially examined as candidates for fore- )
- casting energy consumption are commercial customers, residential house- l
- holds, population, person per household, real personal income, real per- l
- sonal disposable income, per capita income of Massachusetts, total per- )
{_ sonal income of Massachusetts, average real price of electricity, average 1 I i ( real price of gas, lagged real price of electricity, heating degree days, cooling degree days, non-manufacturing employment, gross state product, , , gross national product and the dummy variable. , l l \ Discussion of the Hearession Results l
! 1 i A number of regressions were carried out employing different variables i in the demand equation. The following present the preliminary regression results of various equations. The numbers in parentheses below the coef-ficients are the individual F statistics. All the variables listed above ) ! are included. l \ \
l l A. SALE = 17724.32 + .02853898 RHH + .1009761 CUST + .02359797 GSP - (1220.690) (24.356) (17.479) l $j I 2.036517 LTYPB l (7.778) 2 i R = .996 overall F = 1028.35805 D.W. = 2.95433 - inconclusive B. It is our purpose to select the best combination of variables to explain
- i. the relationship between BECo. sales and economic activity. Different C variables were deleted to discover the most satisfactory result:
h ! l
. In the following equation, residential households, the first selected variable in A, was excluded to find a new set of independent variables.
SALE = 52.44632 + 4.642533 GNP .3919606 HDD 2 (465.251) (6.909) i, R = .975 overall F = 322.73 D.W. = 1.19794 - incouelusive C. In the next equation GNP, the first variable in B was excluded. j The same result as A occurred. D. In the following equation both RHH and GNP were taken out. 4 SALE = 3542.931 + .01294031 ENE + 388.7309 DY i (150.403) (6.611)
! (465.251) (6.909) 2 D.W. = 2.00664 - no serial ! I R = .959 overall F = 187.30 i - correlation j, E. In the following equation, RHH, GNP, RNE, the first chosen variables ' ; in A, B and D were eliminated, the new equation is:
SALE = 577.9235 + .2043917 TPIM + 522.5634 DY .3538169 HDD (287.259) (25.634) (6.281) 2 D.W. = 1.26322 - inconclusive R = .980 overall F = 254.72 i , 1 1 i
*% .s e -,- - - - - - - - - -
. F. In addition to those variables in E, DY was also taken from the equa-tion. THe result is:
SALE = 18743.72 + .2828791 TPIM .01313687 POP .4468053 HDD (486.235) (30.861) (12.062) 2 R = .982 overall F = 288.13 D.W. = 1.47088 - inconclusive G. Another transformed linear equation, double-log, can also explain the demand function - the Cobb Douglas production function which is most frequently used as a demand function in economics. Natural logarithms were calculated on all the variables. LNSALE = 5.579955 + 1.918821 LFGNP + .03032361 LNRPI (4.510) (383.066)
. R = .980 overall F = 409.32668 D.W. = 0.64784 - serial cor-relation exists H. In the next equation LNGNP was excluded.
LNSALE = 76.20982 + 5.158314 LNREE + .6009672 LNGSP (1389.146) (124.834)
+ .9432202 LNCUST , (4.490) r- R = .996 overall F = 2026.65 D.W. = 1.91724 - no serial correlation I." LNGNP and LNRHH were both taken out of the following equation:
r.NSALE = 9.018037 + 2.211818 LNTPIM + .1342129 DY .6452468 LNHDD
, (740.238) (20.718) (7.831)
R* = .990 overall F = 511.24313 D.W. = 1.33151 - inconclusive As a whole, all the equations performed well except: G. Whose D.W. test indicates the exiatence of serial correlation, and H. Whose individual F shows that LNCUST is insignificant. Among all the equations, the A equation was selected. I s l l SALE = 17724.32 + .02853898 RHH + .1009761 CUST + .02359797 GSP -
- 2.036517 LTYPB RHH = Residential Household l CUST = Commercial Customer ]
GSP = Gross State Product i l LTYPB = Lagged average real price of electricity This equation was selected because it corresponds to a priori expec-tations both theoretically and statistically:
- 1. It is felt that the independent variables chosen in this equation accurately reflect the changing economic conditions in the BECo.
i l l l
l 2 service territory. Specifically, a demand equation incorporating a price variable may be best interpreted as the true behavior equation for electricity consumers. ]
$ 2. The coefficients on each variable have the predicted signs and are *. statistically significant at the 95% confidence level. This is an indication that the variables are valid and the regression coeffi- > cients are accurate within the 95% level.
- 3. The high R2 = .996 and F = 1028.35805 indicate a high correlation between sales and the set of indepenlent variables.
, , l )( 4. The Durbin-Watson test as to the existence of serial correlation is inconclusive at the 95% le al of significance. 1 l ; 5. No significant multicollinearity exists between the independent vari-ables. j j I L 6. The sum of the percentage of deviation between the actual sales and l !/ model predicated sales is .01% which is the smallest among all the equations as shown on Table 4 l l Therefore, it can be concluded that this equation is a significant and meaningful regression equation that can be used for forecasting ! purposes. The forecasting equation having been determined, forecast values for each of the fndependent variables must be estimated. The number of residential households (RHH) is forecasted in the demographic section of the forecast, and - is expected to grow from 530,157 households in 1979 to 599,660 in 1989. Commer- ]. !'- cial custcmers have been forecasted through regressions of five years of data by rate and, in special cases, expert territory knowledge. Consercial customers j (CUST) in the BECo. service area are expected to grow from 63,622 (excluding - duplications and C, C-1 and K) in 1979 to 72,299 in 1989, an equivalent compound annual growth of 1.3%. Typical bills are estimated for the 12 kW and 1500 kWH level of demand. The forecasted values are taken as the real growth in average price in the BECo. service area. This real growth is then applied to the 1979 l real value of the typical electric bill. The typicar electric bill is expected j to have real growth from $83.28 in 1979 to $92.30 in 1989, an equivalent com-pound annual growth of 1.03%. Gross state product is essentially measured by employment and the respective wage rates. Wage rate forecasts were unavailable. As a surrogate, employment growth in Massachusetts was taken from the NEPOOL i Model. Gross state product is expected to grow from 30,377 in 1979 to 33,130 i5 in 1989, an equivalent compound annual growth of 0.9%. The values for each of 'I- the independent variables are shown in Table 5. The results of the model, using the inputs in Table 5 are shown in Table 6. t At this point in the calculations, the impact on long-run price elasticity has not been factored into the forecast. We have assumed a long-run price elastic-j ity effect of -1.0 and that all (including short and long-run) of the expected ' elasticity effects are spaced equally over ten years with no additional effect in the first year. This assumption is in good agreement with recent history which shows the commerc2.al sector is relatively unresponsive in the short-run to price changes. The calculated long-run price elasticities are presented in l
. . s ... . . _ _ . _ - . _ ;
. E l Table 7. The overall long-run effect shown along the bottom of Table 7 is then applied to the model produced results. This calculation and result is shown in
. Table 8 as the consercial forecast without adjustments.
e There are several more after the fact adjustments to the commercial sector; { each of these adjustments is shown in Table 8: Consumption of rates C, C-1 and K - The future consumption of rates C, C-1 { and K is forecasted within the residential sector because it has residential ( characteristics. However, it should be added back into the causercial for2 cast to agree with Company reporting procedures. Therefore, in each year of the forecast period, the commercial sector should be incressed by 283 GWH. (' Conservation - Mandated conservation was estimated for the commercial sec-tor in the April 1, 1979 forecast and is again being applied this year. The i effect of conservation will be a reduction of 118 GWH in 1989. Masco - The addition of Masco generation in mid-1981 will reduce the com-mercial sector by 10 GWH in 1981 and 20 GWH thereafter. L Efficient Motorg - The effect of advances in technology in the field of motor controllers and more efficient motors has been estimated for this fore-cast. The coumarcial sector is reduced by 7 GWH in 1989. The resulting forecast after the adjustments discussed above is shown in Table 8. Conserciti consumption is expected to grow from 4,550 GWH's in 1979 to 5,964 GWH's in n equivalent -aspound annual growth of 2.77.. n 1 i ( i I 4 s l 1
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- 78B -
. .s ..
7_, r- TABI.E 1 I PRICE INDEX ' ~ BOSTON, MASSACHUSETTS r Producer Price Inder Consumer Price Index i 72=100 72=100 I PPI CPI r 1960 79.7 68.1 , i 1961 79.4 69.0 1962 79.6 70.5 1963 79.3 71.9 ( 1964 79.5 72.9 1965 81.1 74.4 g t 1966 83.8 76.9 1967 84.0 78.7 1968 . 86.1 81.9 1969 89.4 86.6 1970 92.7 91.8 ( 1971 95.7 96.5 1972 100.0 100.0
- 1973 113.1 --
106.0 1974 134.4 117.0 1975 146.9 127.5 I 1976 153.7 137.3 ( 1977 163.1 144.3 { (, 1978 175.7 151.6 t i r L
, - ..s -- ___ s .. _
r r - r~~ -- -- - - -__,. ,. TABLE 2 ' BOSTON EDISON COMPANY ., CANDIDATE VARIABLES FOR BECO. ECONONETRIC HODEL Description Units Source Variable From To kWh x 10 BECo. Director's Reports SALE 1960 - 1978 BECo. Commercial Energy Sales
- 1978 Average Annual Commercial Customers Customers BEco. Customer Count Sheets CUST 1960
- 1978 Average Annual Residential Households Customers BECo. Customer Count Sheets RHH 1960 POP 1960 -
1978 BECo. Service Area Population CSP 1960 - 1977 Cross State Product - Hassachusetts Hillions (Constant Federal Reserve Board 1978 72 Dollars) TYPB 1960 - 1978 Average Typical Commercial Electric $ (Constant 72 Typical Electric Bills FPC Bill (12 kW/1500 kWh) Dollars) BECo. Service Area Non-Hanufacturing Division of Employment BNE 1960 - 1977 Security 1978 Employment Commercial Non-Heating Price $ (Constant 72 Boston cas Company o, CAS 1961 - 1978 c) Dollars) a 1960 ($/HCF/ Customer) HPI 1967 - 19 BECo. Service Area Real Personal Income Billions (Constant 72 Dollars) RPD1 1967 - BEco. Service Area Real Personal Billions (Constant Disposable Income 72 Dollars) PCIH 1960 - 1978 Per capita Income of hassachusetts $ (Constant 72 Dollars) TPIH 1960 - 1978 Total Perdonal Income of Massachusetts Hillions (Constant 72 Dollars) PPM 1960 - 1978 BECo. Service Area Person per Household Calculated POP - RdH LTYPB 1960 - 1978 Lagged Average Typical Commercial $ (Constant 72 Calculated Electric Bill (12 kW/1500 kWh) Dollars) GNP 1960 - 1978 Gross National Product $ (Constant 72 Dollars) DY 1960 - 1978 Dummy Variable 0, 1960 - 1973 1, 1974 - 1978 Annual Heating Degree Days Degree Days Local Climatological Data, HI)l) 1960 - 1978 Boston, Mass, National Oceanic and Atmospheric Administration
J J TABLE 2 (Continued) Va riable From To Description , Units Source Annual Cooling Degree Days Degree Days Local Clinotological Data, CDD 1969 - 1978 Boston, Mass, National Oceanic and Atmospheric Administration A Natural Logarithm of SALE B Natural Logarithm of CUST C Natural Logarithm of RHH D datural Logarithm of GSP E Natural Logarithm of TYPB F Natural Logarithm of BNE G Natural Logarithm of POP i H Natural Logarithm of CAS am I Natural Logarithm of HPI
" J Natural Logarithm of RPDI ' K Natural Logarithm of PCIM L Natural Logarithm of TPlH H Natural Logarithm of LTYPB N Natural Logarithm of PPN -
0 Natural Logarithm of GNP P Natural Logarithm of HDD Q Natural Logarithm of CDD i i I
- r r-~ # --- - , n . - . , n _ __ ,. , .
O TABLE 3 BOSTON EDISON C(MPANY HULTIPLE SEG8ESSlom ANALYSIS DATA SASE , CSP SPI SPDI Trill GilP SILLIONS SILLIONS PClli NILLlolls BILLIONS LTYPe S4ll IIILLloNS T3PS CAS VAklABIE bWI, a 10 6 CUST Sell 19P _. _ $ $ SWE $ $ $ $ $ $ Imp @ DJ $ PPE 59.423 438,389 1,530,684 19,631 104.43 382,053 342.33 3,576 18,448 736.4 5,627 e 303.63 3.4956 1960 1250.7 e 304.43 3.6845 1358.2 60,620 442,135 I,540,629 20,567 105.15 386,261 356.62 3,648 19,648 755.3 5.828 1968 e 305.85 3.6693 60,722 445,694 1,546,254 21,833 104.79 392.735 373.63 3,7 36 IS,667 799.8 5,994 196; 1430.7 5,754 e 564.79 3.4445 1518.4 60,249 449,972 1,557,878 22.654 104.8% 393,744 345.57 3,752 20.456 838.7 1963 5,854 e 864.84 3.4335 1964 1688.9 60,162 453,359 1,557,500 24,Ill 104.45 397,060 390.16 3,865 21,838 874.4 25.369 98.73 406,388 400.37 4,007 22,047 9 25.9 6,154 e 164.45 3.4233 1965 1773.5 60,488 456,687 I,563,822 5,593 8 98.73 3.4476 1966 1939.7 60,708 460.373 1.568,748 26,646 95.43 422,304 384.32 4,370 23,082 988.8 12.578 18.075 4.343 24,282 1007.7 6,153 0 95.43 3.3924 1967 2131.2 60,536 464,084 1,574,359 28,173 92.82 439,058 394.32 5,986 e 92.82 3.3645 2316.7 60,869 469,605 1,579,975 29,o64 90.56 453,650 394.39 13.175 11.390 4.531 25.459 1058.8 1968 98.56 3.3280 30,981 87.22 477,234 394.89 13.561 11.629 4,688 26,492 3078.8 5,642 746 e 1969 2556.2 68.866 476,443 I,585,590 5,852 Sie e 87.22 3.3005 1970 2788.4 60,692 485,254 1,601,559 31,409 84.18 478,593 415.08 13.787 II.931 4,658 26,578 5875.3 60,736 487,350 1,589,556 32,856 85.58 468,141 433.46 53.713 II.976 4,638 26,713 1107.5 5,738 849 e 84.88 3.7616 1978 3063.0 5,912 678 8 85.58 3.1784 1972 3182.9 60,486 499,712 1,584,793 32,978 84.05 541,982 455.03 14.254 12.276 4.886 27,882 1878.% g 60,072 509.099 1,590,168 31,408 71.55 545,764 445.14 14.436 12.693 4,908 28,494 1235.0 5,139 904 4 84.05 3.1225 1973 3552.9 5,658 646 I 72.55 3.0498 3460.5 59,909 516,634 1,575.263 27,786 64.94 547,052 440.28 14.249 52.240 4,843 28,885 1217.8 [3 1974 68.94 3.0435 1975 3665.4 60,330 519,159 1,580,045 27,195 76.25 529,838 492.00 13.907 18.985 4,762 27.701 1202.3 5.573 862 1 68.207 518,879 1,556.409 24,291 88.88 522,504 550.33 14.028 12.278 4,802 27,818 1273.4 5,499 895 5 76.25 2.9996 8 1976 3869.0 5,323 897 I 88.88 2.9967 3997.6 62,882 520,890 1,560,958 29,309 79.49 537,696 531.27 14.686 12.784 4,992 28,843 1348.5 1977 79.49 2.9678 4 39 / 63,068 524.472 1,556,886 29.928 83.78 560,817 562.60 5,227 30,179 1399.2 5 See 664 I 1978 l
o e* .. l I l
'- TABLE 4 I
BOSTON EDISON COMPANY 1 l' COMMERCIAL ENERGY FORECAST MODEL OUTPUT VS. ACTUAL (1960-1978) i Actual Predicted % Sale Sale Residual Dev. i j 1960 1250.7 1250.4 .3 .02
. 1961 1351.2 1287.6 63.6 4.71 I <
1962 1430.7 1427.9 2.8 .20 1963 1518.4 1522.3 -3.9 .26 I 1964 1611.9 1644.5 -32.6 -2.02 1965 1773.5 1800.8 -27.3 -1.54 1966 1939.7 1972.0 -32.3 -1.67 g 1967 2131.2 2103.3 -27.9 1.31 (-
, 1968 ,
2316.7 20J5.1 -18.4 .79 i 1969 2556.2 2594.2 -38.0 -1.49
' 2788.4 2816.3 -27.9 -1.00 1970 f 1971 3003.0 2904.6 98.4 3.28 1972 3182.9 3248.4 -65.5 -2.06 1973 3552.9 3440~7 __
112.2 3.16 1974 3460.5 3577.2 -116.7 -3.37 l t [ 1975 3665.4 3665.0 .4 .01 e 1976 3869.0 3776.7 92.3 2.39 4 i 1977 3997.6 4015.8 -18.2 .46 ( l ( 1978 4139.2 4156.3 -17.1 .41 ( TOTAL .01 e
. .s ,, ~
TABLE 5 BOSTON EDISON COMPANY 1 FORECAST VALUE FOR INDEPENDENT VARIABLES RHH CUST GSP LTYPB 1979 530,157 63,622 30,377 83.78 1980 537,766 64,731 30,407 83.28 1981 545,785 65,573 30,556 91.77 1982 553,412 66,413 30,856 93.88 1983 560,739 67,254 31,185 89.56 1 1984 567,837 68,094 31,544 94.22 1985 574,801 68,935 31,903 96.11 l 1986 581,117 69,777 32,292 93.99 1987 587,367 70,618 32,592 200.57 {~ 1988 593,549 71,458 32,861 97.96 1989 599,660 72,299 33,130 92.76 i 1990 605,710 73,140 33,340 92.30 t [. 1991 611,037 73,984 33,519 92.30 1992 616,037 74,824 33,699 92.30
~~
1993 620,685 75,664 33,878 92.30 ' 1994 624,879 76,505 34,028 92.30 1995 628,948 77,346 34,208 92.30 1996 632,869 78,187 34,417 92.30 s 1997 636,337 79,029 34,657 92.30 (
- 1998 639_,629 79,869 34,896 92.30 1990 642,727 80,712 35,165 92.30 2000 645,889 81,551 35,435 92.30
l
-. t r -'
TABLE 6 BOSTON EDISON COMPANY COMMERCIAL ENERGY FORECAST MODEL OITTPUT , Model Forecast % Growth 1979 4,376.34 5.73 .i 1980 4,707.19 7.56 1981 5,007.31 6.38 1982 5,312.57 6.10 1983 5,623.16 5.85 l 1984 5,909.53 5.09 r 1985 6,197.82 4.88 1986 6,476.60 4.50
; 1987 6,733.57 3.97 1.
1988 7,006.46 4.05 i f' 1989 7,282.72 3.94 1990 7,546.21 3.62 1 { 1991 7,787.68 3.20
, 1992 8,019.45 2.98 4 1993 8,241.14 2.76 l
1994 8,449.29 2.33 1995 8,684.58 2.78 1996 8,856.34 1.98 i. 1997 9,045.99 2.14
' 1998 9,230.40 2.04
, 1990 9,410.28 1.95 2000 9,591.61 1.93 1
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e , TABLE 8 . DERIVATION OF f.0HHERCIAL FORECAST Coannercial Commercial Forecast Forecast Add Reduction From Long Run Without C, C-1 & K Less Less From Hore Commercial % Equation Elasticity Adjustments Consumption Conservation Masco Efficient Hotors Forecast Growth 1980 4,707,190. .940 4,424,759 283,000 74,160 0 860 4,632,738 1.8 1981 5,007,310. .921 4,611,733 283,000 111,627 10,000 1,290 4,771,816 3.0 1982 5,312,570. .909 4,829,126 283,000 112,401 20,000 1,580 4,978,145 4.3 e 1983 5,623,160. .893 5,021,482 283,000 113,175 20,000 2,120 5,169,187 3.8 1984 5,909,530. .878 5,188,567 283,000 113,949 20,000 2,490 5,335,128 3.2 1985 6,197,820. .862 5,342,521 283,000 114,723 20,000 3,220 5,487,578 2.9 1986 6,476,600. .847 5,485,680 283,000 115,497 20,000 4,030 5,629,153 2.6 1987 6,733,570. .831 5,595,597 283,000 116,271 20,000 4,940 5,737,386 1.9 I 1988 7,006,460. .816 5,717,271 283,000 117,045 20,000 5,900 5,857,326 2.1 1989 7,282,720. .80 5,826,176 283,000 117,819 20,000 6,960 5,964,397 1.8
=
2 a e 4 4 6 1 i INDUSTRIAL J t~ I e J f
- O I
t e
o ** .*
] _
1 I
. Industrial Energy Forecast 2
. 1980-1989 1
l The 1960 Industrial Energy Forecast employs a methodology that is primarily i ,_ the same as that utilized last year. The product of two measures of economic l acitivty, energy intensiveness and employment, yields a disaggregated forecart of
; energy usage by 19 two-digit industrial SIcel for each year of the forecast period.
I Some improvements have been made in the methodology for estimating the economic i activity variables which are described below. Rather than using a tri-county employment forecast, as was done last year, a territory specific employment forecast was dev21oped using data obtained from
- the Massachusetts Divi,sion of Employment Security. This eliminates the need to i* make the assumption that employment by SIC follows the same patterns within the service territory as the tri-county area.
i An estimate of energy intensiveness, measured in megawatthours (MWH) per
; employee, was adjusted by the BEco.2 price forecast and developed using the NEPOOL
- Model which estimates energy and economic variables based on utility data collected on a state-wide basis. Once the energy intensiveness variable is determined, annual
! growth races are calculated from 1980 to 1989 for each SIC. These growth rates i are then applied to the 1978 actual energy intensiveness data for the Boston Edison j territory. Underlying this premise is the assumption that there is little differ-
! ence in labor productivity and levels of technology between the Boston Edison
- territory and the state. This hyopthesis seems intuitively acceptable when con-J sidering the fact that Boston Edison industrial energy sales comprise approximately t
i one-fifth (20.4% in 1978) of the state energy data used to derive the energy in-tensivenessi variable in the NEPOOL Model. hf
- The forecast is then completed for each SIC by calculating the product of the territory specific employment forecast and the energy intensiveness forecast for the Boston Edison service territory. This produces an annual megawatthour fore-j cast for each SIC that has been adjusted for price elasticity effects. These j figures are then further modified for cogeneration, mandated conservation and new q
technology. Specifically, the resulting energy grows from 1,758 gigawatthours (actual) in 1979 to 2,093 gigawatthours in 1989. This represents un average annual growth rate of 1.8%. s Figure 1 is a flow chart of the methodology. ! l Table 1 shows historical and forecast MWH energy sales and growth rates. f t SIC = Standard Industrial Code
~
BECo. = Boston Edison Company + l \ ( _ __ ,I
o .. ,. FIGURE 1 l INDUSTRIAL ENERGY FORECAST METHODOLOGY ( t i I l , , Price Forecast I Input To j f~ NEPOOL Model 4 e i ( s e ,_ i I Industrial Employment ; Industrial Consumption l For State For State 1 i P Employment Growth Energy Intensiveness Rate For State For State l l
\
l Weighting Factor 1978 Actual Energy l Adiustinents Intensiveness For j S rvice Territorv i I { Employment Data For i Service Territorv i t-4 -
) ;
Employnent Energy Intensiveness
! Forecast For Forecast For j
Service Territory Service Territory i , I l
} Regf onal Economic Specific Industry I Outlook Knowledge i
( - s Industrial Energy e j e Consumption Forecast \ 1980 - 1990 i
' s% n n ! ' Alternative Cogeneration j [, Energy , > l 4 i l ? Conservation )
l 1 1
FIGURE l-A o O , INDUSTRIAL CLASS CONSUMPTION N..............,........................,.................................................. i . . . . . . O . . . . . . o,. t . . . . . . 4 o,, . i c,,, . . . . . . . . . . . . ............. . . . . . . . . . . . . .. , i .......... . . ............. . . . . . . . . . . . . ............. l c . c, . . . . . . . C : : : FORECAST l l O . . . . . . O ............'.. . C3 1813 . : s . . . . .
- x. . .
; O .
.c, . . . . . . . . . . . ............. .......... . . ............. . . . . . . . . . . . . ............. .............
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. . . . . . . 1 I . . . . . j
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. . . . . . l C3 . . . . . . .
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! . . . . . . . l
. . . . . . . 1 C3 . . . . . . .
3 5 3 3 3 3 5 9968 1972 1976 1980 1984 1988 1992 1996 YEARS l
- 8 9A -
l
= e, ,.
r TABI.E 1 1 1 j~ INDUSTRIAL ENERGY FORECAST Forecasted Energy and Growth Rates
'~
GIGAWATrHOURS Year Actual Forecast % Growth i 1970 1,813 + 1.1 1971 1,860 + 2.6 i 1972 1,939 + 4.2 1973 2,026 + 4.4 1974 1,753 -13.4 1975 1,679 - 4.2 1976 1,739 + 3.6 t 1977 1,759 + 1.2 1978 1,728 - 1.8 1979 1,758 + 1.7 1980 1,745 - 0.7 1981 1,772 + 1.6
~
1982 . 1,813 + 2.3
. 1983 1,835 + 1.2 1984 1,869 + 1.9 - 1985 1,894 + 1.3 1986 1,921 + 1.4 1987 1,964 + 2.2 i , 1983 2,027 + 3.2 1989 2,093 + 3.2 1990 2,142 + 2.3 l.
1 s,.. l
, a ** ..
i
' METHODOLOGY Summarv 1
- ,,~
The basic premise incorporated in the 1980 Industrial Energy Forecast is
!l that variations in the amount of energy consumed by the industrial class of i ! customers can be explained by variations in the level of economic activity. ! Stated mathematically, industrial energy sales are a positive function of the li level of economic activity. In this year's forecast, as in last year's, the j j best available measures of economic activity are employment and electric energy 1 intensiveness. The general formula for the industrial energy forecast is as i , follows:
i i, I i 4
- ij "( )
n ij ij i . 1 a l' where,
- NWH g
= megawatthour Sales in the Boston Edison territory in year i to SIC j.
(NWH,/EMP,)
= energy intensiveness in meagwatthours per employee in year i to SIC j.
] (EMP)g3
= number of employees covered by employment security 4 in year i to SIC j.
1 Essentially, this methodology is representative of thet used in 1979 but i with some important improvements made in the employment forecast. First, the j employment forecast this year is territory specific, meaning that it is a fore-cast of the number of covered employees from 1980 to 1989 for the 40 cities and - towns of the service territory. In 1979, the employment forecast utilized data ! on the tri-county level, which was then adjusted downward in an attempt to fore-ia. cast territory employment through the use of an adjustaant factor based on energy l sales. The second improvement involves adjustments that were made to account for i ; compositional differences between state and the service area employment growth !{ rates as forecasted by the NEPOOL Model. The reader should refer to the employ-ment forecast section of this report for a more detailed discussion of this issue. i I Enersty Intensivarseas Forecast l As was mentioned above, megawatthours per employee ()STH/EMP) is used as a i , proxy for economic activity in the forecast methodology. This variable was de-j [ veloped using two distinct parts of the NEPOOL Model, namely the Industrial Power Submodule, which forecasts annual energy for the State and the Demographic / Economic module, from which the employment forecast for the state is obtained. Built into the Industrial Power Submodule of the NEPOOL Model are estimates of industrisi price elasticities for each SIC and a mechanism through which these elaszicities are used to adjust the state energy forecast. The elasticities l
- i
- o% ..
a e-1 1 utilizedintheModelaretakgnfromastudydonebyNERA which recognizes both industry mix and use affects. The elasticity estimates are made at the 2-digit
~
level of disaggregation which are shown in Table 2. l . TEU 2 1 I Long-Range Industrial Price Elasticities 4 J Industry SIC Elasticity Estimate . I 22 Textiles -0.6 i 26 P6per -0.6 28 Chemicals -0.6 !; 29 Petroleum -0.9 ' ' 33 Primary Metals -0.9 All Others -0.3 i The Industrial Power Submodule also recognizes short-run industrial price eins*1eities by using a separate eethodology which accounts for the cumulative and aging effects of electricity price changes occuring over time. Using these price l- elasticity estimates, changes in the consumption of electric energy due to changes in the real price of electricity are calculated using the following adjustment jj {, mechanism:
- = E g( )k ' o 3
i I - where,
~
E" = energy intensiveness (kWH/$ value added) of industry 1 at price level P,. E = energy intensiveness of industry 1 at price P . P = average real price of electricity to industrial
" customers in period n.
P = average real price of electricity to industrial i customers in period o. Eg = price elasticity estimate for indestry i. i t-
'~
Taken from testimony of L. Guth of NERA befor? the Connecticut Public Utility Control Authority and Power Facilities Evaluation Council, March 5,1976. Battelle-Columbus Laboratories, Report on A Model for Long-Range Forecasting of
- Electric Enerry-and Demand, Page 13.
4 e
. *o ..
This mechanism links economic activity to energy usage in the Industrial Sector. It implicitly states that the firms within an industry are able and willing' to adjust their electric energy usage as an input into their production functions if the price of electricity is allowed to vary. For example, if the price of electricity decreases, a firm might choose to substitute electricity for labor or some other substitutable production input in order to produce the same i level of output. How much a firm changes its electric usage in response to a ' change in the real price of electricity is determined by the price elasticity of the industry, E . Some industries have relati;ely high price elasticities, suchasSIC33,prkmarymetals,whoselong-runpriceelasticityisestimatedto i be about -0.9. This means that for a 1% increase in the real price of electricity, f demand for electricity will be reduced by .9% in the long run. Most industries at the two-digit SIC level are relatively price inelastic, having estimated .
. elasticities of -0.3 or less. This simply means that these industries are not as
{ free to vary the amount of electricity they use in their production processes as are other industries. It is believed that this is due largely to the fact that levels of technology require fixed amounts of electrical energy and often change i slowly over time. l In order to utilize this mechanism in the NEP00L Modal, it was necessary to l estimate the real price of electricity for the Boston Edison territory over the forecast period. Adjusting this forecast to 1967 dollars yields the figures shown Selow in: TABLE 3. TABLE 3 L Industrial Energy Price Forecast 1967 - 100
~
- Year c/kWH i
1979 ('Actua11 2.31 1980 2.72 s, 1981 2.78 1982 2.65 1983 2.79 1984 2.84
; 1985 2.91 ,! 1986 3.11 __
1987 3.03 ; 1988 ' 2.87 i 1989 2.86 i When the Industrial Power Submodule of the NEPOOL Model is run using these l s prices both short ano long-run price effects are included in the calculations. l The energy forecast adjusted for Boston Edison prices is then taken and divided by the employment forecast for the State of Massachusetts. Both the employment and energy forecast taken from the NEPOOL Model are at the 2-digit SIC level. This yields a forecast which is a close approximation of energy intensiveness as - measured by megawatthours per employee for the industrics in the Boston Edison service territory. i 1
The major assumption inherent in using the energy intensiveness variable is that the energy intensiveness, measured in megawatthours per employee for the state, is a close approximation of energy intensiveness for the Boston Edisca service territory. In order to do this, underlying assumptions concerning labor productivity and levels of technology must be made. We do not have any reason to believe that the difference in either the level of technology or labor product-ivity between the state and service territory by SIC is significant. Using the above methodology yields the energy intensiveness forecast pre-sented in Table 4. I l l t t 1 - 1 f i L t I
' -'- r- - ------ - - . . . _ . .. ,
t T Ast.E 4 Susteen Edison Campany ForecasteJ t.nessy latensiveswss (Wit / Employee) . {E 1980 - 1990
?.
1982 1981 198% 1985 1986 J}j.7 12.33 J191 1229 M 1980 1981 20.325 20.661 21.157 21.772 22.577 22.964 ". 20 18.758 18.959 19.342 19.648 20.002 10.076 10.292 10.543 10.741 10.954 11.3 % 11.847 12.354 12.837 22 9.616 9.758 1.517 1.569 1.611 1.655 1.695 1.7 38 I.792 1.861 1.929 1.994 23 1.483 3.019 3.071 3.114 3.182 3.252 3.335 3.429 3.591 3.678 3.797 24 3.011 1.602 3.6 50 1.689 1.715 1.745 1.779 1.818 1.873 1.923 1.977 25 1.570 16.016 16.429 16.694 17.027 17.296 17.586 18.141 18.905 19.651 20.362 26 15.908
- 27 4.997 5.026 5.104 5.153 5.215 5.266 5.318 3.411 5.534 5.653 5.;66 28 15.781 16.310 16.575 16.895 17.071 17.274 17.860 18.747 19.604 20.40) 15.659 21.458 21.828 21.911 22.045 22.034 22.073 22.610 23.510 24.363 254135 29 21.679 30 21.860 22.353 22.732 23.142 23.493 23.860 24.408 25.098 25.773 26.427
- 21. % 0 I
5.181 5.305 5.408 5.5tP 5.624 5.733 5.883 6.074 6.257 6.443 e 31 5.!!5 un 11.393 11.432 11.506 11.565 11.632 11.777 11.992 12.194 12.379 e 32 11.371 !!.308 33 9.573 9.327 9.338 9.213 9.133 8.864 8.872 8.944 9.154 9.3% 9.477 34 4.342 4.457 4.520 4.%) 4.614 4.6 36 4.702 4,783 4.849 4.992 5.090 18.450 11.754 12.019 12.238 12.437 12.646 12.951 13.330 13.703 14.065 35 11.234 36 10.771 11 138 11.459 11.806 12.133 12.489 12.926 13.48 13.979 14.504 10.508 37 10.459 10.493 10.676 10.854 11.101 11.293 11.670 12.052 12.511 12.969 14.421 38 14.828 15.254 15.828 16.315 16.880 17.392 17.881 18.515 19.267 20.023 20.775 39 3.282 3.349 3.449 3.535 3.631 3.722 3.816 3.942 4.090 4.248 4.389 i
/
Emplovnent Forecast The 1980-1989 Employment Forecast is based on data on covered employment for the 40 cities and towns of the Boston Edison service territory. This data is available at the two-digit SIC level and provides a territ.ory specific data base. This data base includes all those persons covered under employment security col-lected for each town by place of employment. This does not include govertusent employees, non-profit organizations and self-employed workers. It is not expected that the number of workers not covered under the state's employment security system that fall into any of the manufacturing SIC codes is substantial. The most recent year for which the territory specific data was available was 1977, and it is from this base year that employment is forecasted to 1990. To
! accomplish this, the same territory specific data was collected for 1975, and a 1975 to 1977 growth rate was calculated. Taking employment data for the state l
for the identical years from the NEP00L Model, a second 1975-1977 growth rate was obtained. Dividing the territory growth rate by the state grow.h rate yields a
, ratio which reflects the difference between territory and state growth rates.
This growth rate ratio was calculated in the same manner for each of the 19 in-l dustrial SIC codes. These ratios are then used as weighting factors which are applied to the NEPOOL forecast of employment growth rates. By doing this, we have adjusted the employment growth rates for any compositional differences so that mapping of NEPOOL Model estimates fit better onto the service territory. ! l The adjusted growth rates are then applied to the original D.E.S.* employment i data for 1977 for the 40 cities and towns of the service territory for each SIC. This yields an employment forecast that is territory specific for each SIC from 1980 to 1989. Tables 5 and 6 trace the development of the state and service territory employment growth rates as well as the weighting factor calculation.
, Table 8 shows the weighting factors and adjusted employment growth races. Figure 2 is a flow diagram showing the employment forecast methodology as described above. Table 9 summarizes the employment forecast which utilized the above methodology.
*D.E.S. = Division of Employment Security I
l l
. oo ,.
c i r , [ FIGURE 2 . r EMPLOYMENT FORECAST METHODOLOGY DES Covered Employment NEPOOL Model Employment )
; 40 Cities and Towns By For State By SIC For SIC For 1975 And 1977 1975 and 1977 /
f - 75-77 Employment 75-77 Employment Growth Rate Growth Rate i s Weighting e Factor
% s NEP00L Model Forecast )
. Employment Growth Rates ]
, For The State Of M u sachusetts l 1978-lh90 l
- 4. ;
Adjusted Growth Rates t sp - Employment Forecast i 40 Cities and Towns 1980 - 1989 1 i k s l l r __
* *e ,,
b r* i
' TABLE 5
{ BECo. Employment Growth 1975-1977
}
1975 1977 Growth BECo. BECo . Rate
, SIC code Emplovnent Emplovnent BECo. Service ! , 20 12.283 12,027 .0208
{ 22 3,230 2,838 -.1214 I 23 10.093 10.529 .0432 24 825 1,165 .4121 25 1,488 1,308 .1210 i 26 7,107 7,310 .0286 j 27 16,527 16,651 .0075 28 3,541 4,106 .1595 t 29 227 426 .8767
, , 30 3,447 3.557 .031?
31 2,208 2,126 .0371 32 1,227 1,261 .0277 33 1,655 1,675 .0121 34 11,822 11,694 .0108 35 14,199 17,263 .2158 f 32,572 38,927 .1951 36 37 6,819 8,803 .2910 38 13,281 20,120 -- .1006 39 2,607 2,577 .0115 r i t. i i 4 6..
* *~ ..
r-t t
. TABLE 6 i'
i State Employment Growth 1975-1977 7 t 1975 1977 Growth State ' State Rate Fcr Employment Employment State SIC Code 20 29,399 27,768 .0555 22 23,499 24,060 .0239 f 23 40,007 39,930 .0019 24 4,100 5, 34 2 .3029 25 4,300 8,464 .0197 26 27,299 29,692 .0876 27 39,701 41,672 .0496 28 14,900 15,380 .0322 29 1,000 1,026 .0260 30 28,202 31,163 .0150
' 19,648 .0370 31 20,402 32 .
12,502 12,562 .0048 33 9,849 10.260 .0365 I- 34 43,298 43,782 .0112
- 35 75,696 80,151 .0589 36 79,609 82,689 .0387 37 21,000 22,407 .0670 38 41,396 42,594 .0289 ; ~~
39 25,097 26,024 .0369 t p s s I i
i i - TABLE 7 t- ' BEco. Employment Growth 1975-1977 t a Employment
; j Weighting
, ( SIC Code . Factors 7 20 .3748 l *
- 5.7950 22 I 23 -22.7368 24 1,3605 4
25 - 6.1421 4 26 .3265 1
- 27 .1512 g
! 28 4.9534 29 33.7192 30 .3038
. 31 1.0027 32 5.7708
{ l- 33 .3315 34 ,
- .9643 r
35 3.6638 36 5.0413 37 4.3433 i j _ i 38 3.4810 I 39 .3116 .1 l L .. l .. , 4 - i
)
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- I BEco. Service Tarritory
- 1980-1990 198 1987 1988 1989 1990 r SIC 1977 1978 1979, IMO 1988 19_82 198J 1,985 19J8 11, % 7 11,350 !!,034 10,890 10.760 10.642 10.525 10.400 10,286 20 12.027 31.871 !!,659 18.487 11.191 2.862 2.837 2.837 2.837 2,837 2,837 2.839 2.441 2.844 2.849 2.857 2.468 .
22 2.8 38 2.829 , 10,058 9,865 9,672 9.442 9.296 9,098 23 10.529 10,6C2 10.537 10.651 10.586 10.482 60.353 10.201 1,217 1,307 1,333 1.358 1,380 1,395 1.403 1.403 1,406 24 1,165 1,786 1.182 1.251 1.278 1,365 1,361 1,368 1,379 1.370 1,382 1.396 1.410 1,422 1,422 25 1.308 1 .34 7 1.385 1.355 7.691 7.737 7,775 7.798 7.829 7.461 7.900 7,%7 7.963 26 7,310 7.457 7.479 7.569 7.630 17,308 18.063 18.442 18,848 19.262 19.686 20.099 20.521 20,951 27 16.651 17.017 17.102 17.481 17.743 4,140 4,112 4.096 4.105 4.131 4.178 4.24 0 4.315 4.401 4,503 4,621 4.713 28 4,106 4.151 443 449 448 446 443 439 4 34 429 424 418 412 405 398 29 426 3,672 3,738 3,794 3.462 3,935 4,018 4.106 4.205 4,314 4.439 4.577 4.738 30 3.557 3.625 i ' 2,228 2,219 2.206 2.186 2,162 2.134 2,100 2.060 2.017 1.917 1,888 e 31 2,126 2.192 2.219 O 32 1,261 1.%8 2,004 2,021 2,038 2,049 2,066 2.097 2.139 2.191 2.249 2.310 2.376 2.424 e 33 1.675 1,725 1,723 1,728 1.734 1,74 0 1,753 1.765 1,772 1.786 1, G 'O 1.817 1.828 1.831 34 11,694 12,169 12.349 12,471 12.595 12,620 12,593 12.555 12.530 12,517 12.492 12.449 12.517 12.479 18,688 18.888 19,220 19,420 19 % 0 19, 4 2 19.742 19,823 19.904 19,985 20,066 35 17.263 17.%0 18.352 38,927 41,682 41,829 42.134 42,357 42.582 42,808 43,035 43.263 43.626 44.0 % 44,221 36 41.052 41.397 37 8,803 9,234 9.263 9.388 9,516 9.5% 9.54 7 9.474 9,410 9.392 9.374 9.403 9.472 9.501 20,120 21,469 22,048 22,005 22.231 22,485 22.741 23.046 23.332 23,766 24.281 24,531 38 21.097 21.757 2.721 2.724 2.713 2.702 2.680 2.658 2.626 2.576 39 2.577 _1M 2.649 2.692 _ 2.6% 2.788 170,596 175,394 176.235 177,035 177.825 178.774 179,702 180.972 182,507 183,353 164.363 171.890 173.347 174.530 I i.
e .. .. - 3 Industry Summary e- Although the 1980 industrial energy forecast is disaggregated by 19 two-l . digit SIC categories, the 5 leading SIC's represent approximately 74.7% of total industrial sales. This is mannarized below in Table 4 for the forecast year - i , 1980. . Y. i TABLE 10 ]f i
; Leadina SIC's In 1980 j f SIC Forecasted MWH's % of Total Sales
( i SIC 36 Electrical Machinery 437,259 25.0 SIC 28 Instrumenen 322,613 18.5 SIC 20 Food and Kindred Products 216,974 12.4 SIC 35 Machinery, Non-Electric 209,155 12.0 SIC 26 Pulp Paper Products 120,408 6.8 ) 1,306,409 MWH 74.7% i Below is a brief summary of these major SICa followed by plots of each of the 19 SICS for each year of the forecast period. SIC 36 Electrical Machinery i 4 4 This SIC is by far the largest employer and censumer of electric energy on the BECo. system. Included in this SIC are electrenics firms, most notably those
~
I located along Route #128. Consumer demand for calculators, two-way radios, stereo equipment TV receivers, etc. continues to be strong regionally as well as nat-ionally. There are several nationally known makers of these products or producers j of Latermediate goods used in their production on the BECo. system. From 1980 to 1989, l i total energy demanded by this industry grows from 437.259 MWH to 615,859 MWH, an increase of 40.8 or an average annual growth rate of 4.1%. SIC 38 Instruments { SIC 38 is a growth industry with some of the country's best known names L located within the service territory. This SIC includes medical and scientific instruments and supplies as well as photographic equipment. In 1980, we expect I the firms in this SIC to purchase 18.5% of all industrial energy sales. Specifi-
; cally, energy sales to this SIC grow from 322,613 MWHs in 1980 to 486,178 in 1989, an increase of 50.7% or an average annual growth rate of 5.1%. Leading the growth in this industry is the demand for photographic equipment, with one '
of the nations largest and best known names located on the BECo. system.
- 103 -
e s ,s j SIC 20 Food and Kindred Products Nationally, this industry has entered 1980 on a strong footing. There has been a movement towards more frozen snack and light foods which require 4 substantial amounts of energy through utilization of processing and packaging
; capital. We expect this trend to level off. Employment is forecasted to de-
- crease substantially in this industry in the Boston area, from a high of
! 11,567 in 1980 to 10,400 in 1989, a 11.2% reduction. Electrical energy con-i sumption will grow slowly, however, from 216,974 MWH in 1980 to 234,800 in 1989, i r an increase of only 8% or .8% annually.
I SIC 35 Machinerv, Except Electrical i According to the Standard Industrial Classification code, the computer
!. equipment industry is included in the non-electrical machinery SIC and it is ,
f ' from this group of firms in the BECo. service territory that the strong growth in coming years will be derived. The computer industry has always considered itself to be immune to economic downturne because its products helped its cus-tomers increase productivity and reduce costsl. Both employment and energy in-tensiveness are expected to continue to grow solidly as they have in the past. Several up and coming smaller firms are located in the service territory as well as one of the larger mainframe manufacturers. Specifically, energy consumed i ! by this industry grows from 209,155 MWH in 1980 to 273,854 in 1989. This re-l l presents an, average annual grovch rate of 3.09%. i I i SIC 26 Pulp, Paper Products In 1980, this SIC is forecasted to consume 6.8% of total industrial sales. i ; . Nationally, this industrial has fully recovered from the severe downturn ex-i i perienced at the end of 1975. There will be growth in the service territory, and at a pace that will be considered fairly strong. Energy sales are forecasted I to grow from 120,408 MWH in 1980 to 156,166 MWH in 1989, an annual growth race of about 3.9%. Additional Information on Other Industries
! Projections were made for each individual SIC then combined to yield total i energy requirerents. However, it should be noted that for some industries, pro-jections had to be based on historical growth rates modified by specific infor-t mation concerning the industry in the area and specific company information
! concerning a particular user. This information is identified and its impact is discussed below.
i (
" Industrial Outlook", Business Week, January 14, 1980 i
l l
- 104 -
SIC 25 Furnf rure and Fixtures (0.1% of 1979 total Industrial Sales)
< Tri-county employment in this SIC is declining. The evaluation of actual MWH data for the years 1966-1977 shows a pattern of peaks (1971-1972, 25.3%
growth) and troughs (1975-1976, 24.6% decline). Over the forecast period although MWHs show an overall increase, there are fluctuations over time;
; thus, years in which there is a decline. A qualitative conclusion can be made, i for it appears the general tendency is only toward limited growth for this SIC.
In addition, since this industrial class accounts for only 0.1% of total sales [ (1979), it has little impact upon Edison's total industrial sales. I SIC 29 Petroleum Products (0.6% of 1979 total Industrial Sales) t Based on knowledge of the Company's territory, the energy consumption has been held constant at 9,901 MWHs over the forecast period. The sales to this f SIC are so small that any error made by this assumption would be negligible. SIC 31 Leather and Leather Products (0.6% of 1979 total Industrial Sales) The downturn in the leather footwear industry is due, in part, to the rise in imports. In Edison servi,ce area, SIC 31 declined 9.5% in 1976 and 10.0% in 1977 and 11% in 1978. We do, however, expect a slow recovery, with sales fore-casted to reach 11,396 in 1980 (a 2.1% increase over 1979), and growing to 11,994 by 1989, an increase of 5.2% or an average annual growth rate of .5%. SIC 37 Transportation Equipment (5.5% of 1979 total Industrial Sales) , 1 SIC 37 represented 5.6% of 1978 sales. Nationally, economists are predicting l
' a sales downturn of as much as 10% in the automobile industry. In the Edison !
service area this industrial class is dominated by one very large automobile i producer and although this producer may be basically optimistic. about an upward trend in production, at present, it is difficult to determine the effects of higher price tags, the energy problem, and imports on automobile production and the need for workers. Therefore, empirical evidence leads us to the assumption that sales to this SIC will rise to approximately 91,920 MWH in 1985 and remain at about that level for the remainder of the forecasr period. A l l
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- t 1ABl.E 12 INIMJSTRI Al. sal b ST SICA (MECAWATTHOURS)
't Sic 1970 1971 1972 1973 1974 pn 1976 1977 1978 1979**
20 165,001 189,853 193.529 246.428 226.439 228.610 245.822 248.2 % 216,622 215.541 ., 22 23.725 24.831 25.761 *20.284 17.*325 15,773 18.679 20.230 26.755 26.889 23 14.709 14.957 17.050 16,916 15.388 14.813 14.576 14.816 '.4,948 15.225 ;
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24 3.289 3.935 4,112 3.978 3.552 3.538 3.671 3.619 3.476 3.494 l 25 3.968 4.482 5.618 5.660 4.528 3.946 2.974 2.408 2.004 2,129 , 26 103.148 115.814 131.843 129.199 124.859 100,138 104.591 !!8.324 !!6.204 !!7.968 1 27 82.272 84.375 91.108 49.684 83.858 83.862 87.438 87.902 83,543 84,577 28 123.579 132.786 141.372 139.518 134,885 125.333 127.442 91.557 62.514 64,247 29 6,198 10.391 10.485 10.956 11.885 10,429 11.125 10.871 9.901 9.954 I 78,213 77,8te 30 107.639 98.514 99,031 100,658 89.561 71,112 75.401 75.371 o 9 38 15.654 18.443 20.600 17.581 15.312 15.348 13.900 12.505 11.044 11.235 ; e i 32 16.695 12.359 12.989 25.498 24.611 22.302 20.470 21.741 22.392 22.713 ; 33 28,854 34.595 28,610 27.946 27.517 23.723 20,539 18.416 17,658 17.150 34 114.550 83.429 - 72.374 76.374 66.574 60.089 64.742 55.732 54.080 54.710 35 !!8.167 127.821 148,139 152,454 135.545 161.211 178.277 187.900 194.292 193.814 36 521,430 494.434 50 .227 470.528 394.362 409.477 390.820 406.115 412.466 424,744 37 88.708 122,538 124.429 117.943 61.256 61.136 67,988 86,613 96,309 96. M4 38 265.952 278.442 294.955 308.635 269,230 256.866 279,658 288.128 300.240 311.417 39 9.363 9.509 11.580 65.639, 45.744- 9.519 8.217 8.134 8.397 8.657 TOTAL 4.813.171 8.859.825 1.938.812 2.025.801 1.752.431 1.677.225 1.739.175 1.758.647 1.728.265 1.758.448 arson-clamstfled sales allocateJ to math SIC by ratio of the Sic to total reported sales. e.g. In 1970 Sic 20 was allocated , 9.1% of non-clamelfled sales to yleid 140.502 MWHS. eaEstimates non-claustfled
, ~ - ' ' 8SE
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I"~~$ , , j jl Boston Edleon Company i Indnetrial Energy Forecast e Annual HWH S. ales Oy 2-Elgit Sic , 1980 - 1990
/
Sic 1980 1981 8982 1983 1984 1985 1986 1987 1988 1989 1990 , 20 216,974 217.782 221.128 219.88I 220,702 228.339 222.312 225.853 229.850 234,800 232.227 22 27.281 27.683 28.586 29.198 29.910 30.494 31.820 32.329 13.752 35.295 36.816 , 23 15,795 16.059 16.446 16.679 16.883 17.048 B7.145 17.332 17.646 17.938 19 127 , 24 3.664 3.777 3,925 4.070 4,242 4.416 4,602 4,783 5.038 5.160 5.388
- 25 2.084 2,084 2.084 2.084 2.084 2.084 2.084 2.084 2.084 2.084 2.084 .
26 120.408 122.202~ 126.355 129 I68 192.185 134.874 137.680 142.606 149,349 156.166 162.142 27 86.488 87.859 90.560 93.079 96.175 99.254 102.435 106.521 131.228 116.005 120,803 ; 28 17.612 37.682 37,682 37.682 37.612 37.682 37,612 37,512 37.612 37.612 17,682 29 9.901 9.908 9.901 9.908 9.901 9.908 9.908 9.901 9.903 9.90I 9.908 30 80,598 82.937 86,327 89,450 92,984 96,462 100.338 105.296 lit.480 117.963 125.211 31 11.396 II,505 II,703 18.822 II .9 30 12.002 12.049 12.189 12.25I II.994 12.164 32 22.900 23.046 23.344 23.618 24.128 24,737 25.485 26.486 27.701 23.972 30,006 31 16.542 16.173 16.248 16.150 16.820 15.707 15.845 I6.099 16.611 17.066 17.352 34 54.149 56.136 57,042 57.462 57.929 58.089 58.854 59,749 61s073 62.484 63.518 35 209.155 216.268 225.989 233.409 219,375 244.536 249.657 256.728 265,320 273,854 282.228 36 437,259 450.540 469.288 485.369 502.723 519.389 537.464 559.238 588.078 685.859 641.181 37 69.108 78.468 85.194 85.194 85,894 91.920 91.920 91.920 98.920 98.920 98.920 38 322.683 336.320 348,295 362.699 379,547 395.5Il 412.085 438.992 457,899 486.478 509.631 39 8.714 8.950 9.189 9.429 9.666 9.907 10.224 10.539 10.933 II.329 13.723 Sub Total I,752.634 1.805.302 1.869.209 3.916.267 1.974.490 2.025.225 2,078.805 2.148.467 2.238,978 2.332.573 2.410.234 Less cogeneration 0 28,68I 43.363 65.044 86.726 108,407 130.088 158.770 173.451 195.133 216.884 ($ - Handated Conservation 2,518 3.777 3.777 3.777 3,777 3.777 3.777 3.777 3,777 3.777 3.777 OD - Improved Efficiency 5.052 7,619 9.330 12.493 14,786 18.998 23.780 29.867 34.Sil 45.052 47.Sc8
- Total I.745.064 l.772,225 4.812.739 8.834,953 5.869.271 8.894.050 1,928,160 1.963.753 2,026.939 2.092.681 2.848.835 I Crowth (.74) 1.56 2.26 1.23 1.87 1.33 1.42 2.22 3.22 3.24 2.35 l
a
r ec .c . f SIC 20 i O O FOOD AND KINDRED PRODUCTS
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o , t 1 . . . . . . I C3 1 . . . . . r*C3
.%...........J............%.. 2...........
3Y. ............*...........d........e. - - na .' c3 . gy . cg...............,...........
~ . . . .
o g . to. ........................>.......... . . . . . . . . . . . . > . . . . . . . . . . . . . . . . . . . . . . . > . . . . . . . . . . . . . e . 10msr . ; . . . 23725 HISTORICAL; ; - - ;_g : : t o 4. _ .:._ ~_ * ' ~ ~
~ ~
O, . . . . . 5 5 3 3 4 1996 3 3 l 9968 1972 1976 1930 1984 1988 1992 TERRS
-110-i
I l l
.. SIC 23 o
9 o APPAREL AND RELATED PRODUCTS l
- P.............,...................... . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
C3 . . . . . . . c . o . G3
...........s...........
............s.........................s.............'
o .
.= , . . . . . . . . . . . . . .............
c, . . . . . . . C3 * * *
- g
\
ye gp ............*............s........... .'............s.......................
.s.............
. o .
- x. . . . . . . .
i o .
~. . . . . . . . . . . . . ............. ..........
w, .
. zo . . . . . .
x . 3:P c,. ............* ........... ..........
...........s.............. .........s.............. . :
1
. . . . . . . l
. . . . . . . 1 c, . . . . . .
==
o . . . . . . . r o
- l . . . . . . . . .
L.
- o. .
...........s............
............>........................s..............
14709 . . . . . . . 1 :HISTORICAI.l ; FORECAST l l l l o 4 - L--- L o -
**1968 1972 1976 1980 1984 '
1988 1992 1996 TERRS l i
.111-
SIC 24 . f" " O 9 C
. LUMBER AND WOOD PRODUCTS .- =P.............,...................... . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
O . . . . . . o . c,. . . .
.=............:............*............s..............
O,,.
...........s...........
j . c, . .
, O .
c,. . . . . . . . O. . . O, c . . . . . . .
. O . . . . . . .
s.............'. i i O.
. ............c............s...........
c3 .
, c, .
1 O . . . . . . . c,. . .
~ , , .. . . . . . . . . . . . . .
mO . . . . j i ro .
"E O* . . .
E c ,F. ............*............s...........
.............s.............c....... ....s.............*
C3 * *
- C3 O
o . . . . __. . . . m. W
......... . . .p......
.....g.......... ..p...........g.... .
. . . . . . . . .p...........g...
C, . . . . . . .
, o .
O. ........................s........... g .
...........s.........................s..............
3289 : HISTORICAL ; ; : FORECAST : : . c3-O 4---------- .
-------===3 I 4 5 5 5 5 5 9968 1972 1976 1980 1984 1988 1992 1996 YEARS
-112-
i to
. .4 SIC 25 _
i 1
\
O
- 9 O
. FURNITURE AND FIXTURES r.............e...........,..........,.e................................................. , O , . . . . . .
i i O . ( . . t Q . . . . . . . O ............%..e
.e.....J..........e .*............t.............*............J.............'
yn .
. 4 .
j c . . < , Q . i 1 o . . . . . .
. . . . . . . . . . . .e....e...e...,........ee....
I O. . . . . . . . . . . . . .e...e .e.... .......... ..e...........,.. .
=r . . .
l . . . . . . .
- O . . . . . . .
l c . C I O. ............%...........J........... .%...........J.............%...........J.............' . g y . . se . . . C j , . . . . gg . 4 O . . . . . . . O * *
- 1
% . . . . . . . . . . . . ......e......,.
63 . . e... ..... . ..e...........,.
. . . . . . . . . . . .e..........s............. , yC .
l g= o . . r*Q Z:3". ........... %...........J........... .%...........s.............%...........i.............' g .
\ . . . . . . . .
- o . .
O . O * * *
@a. . . . . . . . . . . . . .,....................... ..e...........,.........................g.............
i . Q . . O - - '
- C. ............ ...........>.......... ............J.............. ..... ......>.............
o . l HISTORICAL l : FORECAST l l l 3968 . . . . . . . O 4 . . . . . . . O ' ' ' ' ' '
, 968 l'972 l'976 1980 1985 1988 l'992 1'996 TEARS
-113-1
. i
. % .4 .
SIC 26 r-O 9 O
, PULP, PAPER PRODUCTS r 2......................................................................................
t m . O . . . . . I' o . .
.s C3 U,3,. ............*............s........... ..*............s.............=...........s.............'
o .
, O .
) o . . . . . .
- m. ............. ........... .......... ... ........... ............. . . . . . . . . . . . . . . . . . . . . . . . . .
2 . . . . . . . l . . C3 . . . . . . . C3 . I O . . . . . . . ( f C
.s...........
..s............
O l xa . 1 i O . . . . . . 1 . . . . . . . . c3 . . . . . . . N., ............. ........... .......... ... ........... ............. ..... ..... ... .. . . . . . . . 61 . . . . . . . WO l ro . t* O Z2g ...... ........... ..... .......... o . O . . . . . . . t . . . . . . . . 1 o . . . . _ . .
- m. ....
...........AST
~
HISTORICAL .
. FOREC.
t . . . . . . .
! 103148 -
t . a. - -
~_ . . . .
O .
, o .
+ . . . . . . .
O. ............'............s........... . . . . . . . . . . . . . . . . . . . . . . . . . * . . . . . . . . . . > . . . . . . . . . . . . -
. g .
C3 . . . . . . , O ' 5 5 5 5 5 5 I 9968 1972 1976 1980 1984 1988 1992 1996 TERRS 1
-114-
, SIC 27 O
o
. PRINTING, PUBLISHING !
i- :P.............,................................................,......................... W . . . . . . . 1 o . i o .
. )
o . . .
............a.............*............s.............*
,C . ............
...........s...........
}
1 . . . . . c, . . . .
. O .
> o . . . . . . .
=
.i .
c, . . . . . . . C3 . . . . . o . ( O,.
=
O
, c, . . . . .
o . c,. . . . . . . .
~,_ . . . . . . . . . . . . ............. .......... ............ .. . . . . . . . . . . . . ............. ............. .
w C3 . . . . . . . , I,oc3 . . . . . . . , E:,P. ,
...........J...........
............s.......................s..............
1 c, . . . . . . . g o. . c, . . . . _ . . . g_ ............ ........... .......... ... .. . . ... .... ............. ........... .
- HISTORICAL
- FORECA$.T '.
c3 . . . c3 82272 . . . . m
. - =. , g g
.....".........J........................J..............
l g W
- ..... . . . . . . . . .. . . . . . . . . . = .
g . c3, c . . l I I i 5 5 5 5 1968 1972 197R 1980 198tl 1988 1992 1996 YEARS I \ l -115-l [ I . f I
~ ,, .s i
SIC 28 l l 9 o . CHEMICAL AND ALLIED PRODUCTS
,=,P...................................,.................................................... . c, . . . . . . .
o ,
. c, U,3.,
, ............'............s..........
..*............s.............=............>............*
r., . . . . . . . 1 . . g c,. . . . . . . . ( .. . . . . . . . . . . . . .. . . . . . . . . . . . , . .......... . . ............. . . . . . . . . . . . . ......... o, .
- c. .
c, . . . . . . . ( o,. ........................s...........
..*............s.........................>....
j O x c, . . . . o . 1 c ,. . . . . . . .
~,,. . . . . . . . . . . . . ............. .......... . . ............. ............. ...... .... ............. .
. . . . . . . l o .
. . . . i go .
~x .* . . . . . . .
E 2,,. ............'............s..........
..'............s............
o ' 4 g o . . e
. . . . . . . . . .
- H. I. S.T. O. R. I. C. A. L...........
. 123 79 . c, . . . . . . .
- o. .
o g
; ; FORECAST ; : :
- - .:. - - a .
. . . ---.--- 3 .
c, . . . . . . . C3 . 5 5 5 5 5 5 g ( 9968 1972 1976 1980 1984 1988 1992 1996 YEARS I l
-116-
% 5= ..
SIC 29 e O O
. PETROLEUM PRODUCTS + =F........................g.....'.... . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4 O . . C3 . . .
=. . . .
C3 . . . .
@. ............'............J........... .*............J.............'............J.............'. .
i p . C3 . . . . . . .
< O . . . . . , e . . . .
l c . . .
..p..e........,.
. . . . . . .e.e.....o...,. . . . . . . . . . . . . ..
O. . . . . . . . . . . . . .e........... .. ...... . ... .. .
=r .
C3 . . . . . C3 - C3
.............z.............*........................*
O. ........................s........... . . . . s y . se . O . I . e . . . . . . r yo . i g . e . . . . O *
- 51 . . .
1 , O . . . e { IQ . 3*O . e E 2. ............*........... 2........... ............2.............*............a.............. . . pg . C3 . . . . . . . g . . . . . . j e . . . . ( C3 -
... . . . . . . . . . . . , .. . . . . . . . . . . . .. ......c....,. . . . . . . . . . . . . .
M . . . . . . {* . . . . O . . . . . , o . e O. ............'............J........... .*............J...... ......'...........J.............* . g . f . .
; HISTORICAL * -
FORECAST - O 6198 . . . m m m M M g m m M M M E E. M m M M M
-3 M g
, e__ 5 5 5 I 5 5 1996 5 9968 1972 1976 1980 1984 1988 1992 YEARS , t -117-
. i. ..
SIC 30 ) ' o o
. RUBDER PRODUCTS
.P..............................~.........................................................
=
. o .
o . g (D.
. ............*............o..........
.............s......
.c............s.............*
i . . . . . . . 1 c, . . . . . .
< c.,,.
=
o. o .
...s.............*
,. o. ,. ............'............s...........
..'............J.............*........
C3 . . . . . . .
, c, . . . . . . .
( C3 c,. . . . . . . .
- m. . .
, m e, .
z o. 1 c3 Z:c,'5. ............'............s..........
. ..'............s.............'............s..............
c . . . . .
- o. .
.c, . . . . . . . . . . . . .............
107639 l HISTORICAL l l l l l ; 3 . FORECAST l @ k :. - l l l . l l o.
...m.
-........>.........................s..............
C3 . . . . . . . c3 - 4 5 5 I 5 5 5 5
**1968 1972 1976 1980 19814 1988 1992 1996 9
YEARS k t
-118-d
.1 5 SIC 31 o > 9 . LEATHER AND LEATHER PRODUCTS i ,
o,.........................................................................................
.= . .
o,,. ............ ........ .
..s..........
...................................e..............
t, . . ,, o . . . . c, . . . . .
- o. .
......e...a...
.*............a...
.........=. .........
I
, o,. ............=............
2........... O . 1 . . i . . g o. . . . i ( . . . . . . .
; o . .
~. . . . . . . . . . . . . ............. ......... ........... ... .
, , o . . . . . . .
n.I o . . . Z .* . . .
.*............s...................
' Z ;P. ........... pg ...........t.......... . g ( . o g
- o. ............ ...........>.......... ........................ .
g . l l l l HISTORICAL l FORECAST . 15654 . . . l . . . .
,.-_-._.a.
i o o _ "" __ ~ " .= ___ __ _ a _ . ._-
.a.
_ m l . . . . . . .
. 9968 1972 1976 198G 1984 1988 1992 1996 YERRS ,
-119-l l
l 1
SIC 32 o 9 STONE, CLAY AND GLASS :
)
o,_.......................,............'.................................................. o . o, c c, . . c, . . o,. . . . . . . . . . . . . .............
.o . . .
C,. . . .
..2.............e o,_ . . . . . . . . . . . . . ..........
2.......... .............a................ i n . a .
- , ,o .
( g . . . c,. . . .
~_ . . . . . . . . . . . . ............. ......... .............. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .
mo I go . g C,-
............'.............s.......... .*............s......................
E d_ . 3 , m . . . 4 (' o . .
- o. . . . . . . . . . . . . . ........... ......... . . . . .
- r. . .
C3 . .4 o . o ........................>......... . .
. ...........s............. . .
o . I ! l l HISTORICAL l FORECAST 16695 - - --
; 0@ l o sa _ f,, . .
o , 8 8 8
' E 8 1980 8
1984 8 1988 1992 1996 9968 1972 1976 TEARS
-120-s
O I n ,e SIC 33 o
. . PRIMARY METALS ,
- P.....................................,........................r.. . . . . . . . . . . . . . . . . . . . . . .
c,, c c,. .
@. ............c............s .......... .
.*............s.............*......... ..s.............*
l c, . . . . . . . Q . c ,. . 1
.o. .
C3 . . .
.=............s.............'........ ...s.............*
. . . . . . . . . . . . * . . . ........s...........
O,. O .
, yo . . .
n,,. ............. ........... .......... .............. ............. ....... ... ............. o . . z.x ,. Z:co,'
............a............s...........
5 .
...........s.............
....s..............
c, . . . . . . . c, . . . . . . . c,,. 4 ,. . . . . . . . . . . . . ............. .......... . c, . . . . . c, . . . . . . . e,. c
...........s..........
...........s...................
.....s..............
'.354 . HISTORICAL 3 . . . . .
- FORECAST l
, 9968 1972 1976 1980 1984 1988 1992 1996 i TERRS .
i k -121-l l I q j I l 1 l
SIC 34 1 1 o J 9 o, FABRICATED METALS
.= . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4 c, . . . . . c .
. .c , . . . . . . .
=,. . . . . . . . . . . . . ............. .......... . . ............. . . . . . . . . . . . . ............. ............. .
c, . .
- c. .
, o .
o,,- ........... 4...........J.......... ...
. ...........J.............'....... . ...J.............* .
so * . . . . . . O . g o. ( . . . t o . . . . . . . N. . . . . . . . . . . . . . ........... ......... . . ., . . . . . . . . . . . , .. . . . . . . . . . . . . ...... .... ............. i. mo
, Io . . . . . . .
- r. .
Z :.,.
............ ..*...........z....................
m
....s.............*
i o .
< o . . . .
t . . . . 114550 l l l l l l l l
, o . . .
- o. MISTORICAL l l l l l
. . . l FORECAST
- o. ........ .. . . . . . . . . . . . . . . . . . . ...........>............u.....
e . . o . o . 9968 1972 1976 1980 1984 1988 1992 1996
. TERRS
-122-
SIC 35 o MACHIN o,............................ERY, EXCEPT ELECTRICAL o . o, . s , o . W.
,, ............*............s...........
. .*............s.............%.......
r . . . . . . . c, . . . . . . o .
. . . . . . . . . . . . ........s.... .......... .............. . . . . . . . . . . . . ......... ... ............. .
o . o ............*............s........... .*............s..... ..............
...2.............*
O . go . . . . . . . o . c ,. . . . . . . .
~ ............. .. . . . . . . . . . . . . ....... .............
t m ,, . 1 zo . 2s z w. c
........... : ............:.......... .:. .FORECAS'I :
....... . ........~......................... ;
m .
\
g
. l HISTORICAL : : : : :
i s o . . . - . . .
, W.
M
. . . . . t 118767 . .
\ m . . . e . . .
o . . . . . . . o . o. g ........................o...........
. . . . . . . l o ,
I 5 5 5 5 5 5 9968 1972 1976 1980 1984 1988 1992 1996 TERRS
-123-
I SIC 36 . l 8 . ELECTRICAL MACHINERY
. c>.........................................................................................
c. Q. . . . . . . . . . . . . ............. .......... . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . c 32,143o . O . . . .
. HISTORIC.AL
..F ORECAST .
. x . .
Q . . ( o . .
- c. .... ....... .... .. . ...... .. ........... ............. ........... ............. .
=r . . . .
j . . . . . t . . . . . . . . ln . . . . . . .
, go .
i 3g ., . . . t Z O,3 . .... . . . . . . ........... ..........
.............a........................>.............
4 g3 . . . . . .
- o. .
- c. ... ........ ........... .......... .. ........... ............ -
t ne . . . . . . . e . . . . . . . i . . . . . . . I C3 . . . . . . . o . i O. ... ........ ...........>.......... ............>..................................... . Q ( . . . . . . . c3 . 9968 1972 1976 _ 1980 1984 1988 1992 1996 YEARS
-124-l l
SIC 37 r- o o . TRANSPORTATION EQUIPMENT 2............. ...................... . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . o . e. i . 1 . . . t o............... r . . . . . . . I, o . C3 . . . . . i x.. . o . . . . . . N. . . . . . . .
- m. .
30 . l. ( zeo. . E d. . . . . . . . . . . . . ...... m .
......a...........
. i o
g l . . . . .
=e . . . . . . .
- i. . . . . . .
i HISTORICAL : l l l l FORECAST o . . . . . . . o '.
-m
- o. *..
ao . . . 8 8 7 0 8 . . . '. . . . . . . . . . . d-. ........
..*P..=r.*............'............J............'
o . . . . . . . o , . 5 I 5 5 5 5 5 9968 1970 1976 - 1980 1984 1988 1992 1996 TERRS
/
-125-
i SIC 38 4 Y o
, =
. INSTRUMENTS AND RELATED PRODUCTS
' r :P.............,...................... , , . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . ,
. o .
- o. . . .
i o,, . o . . . . t . . . . . . . . . . . . ............. .......... ......... ,
- o. . .
o . . . . . . . i o, . 4 t = . 1 FORECAST Xo . . . . . . g n . C ( N. 61
............l HISTORICAL : .
l
\
s . . i
! e coo : : : :
q ro , . . . . .
"I o* 265952 : : : :
.*............s.........................s..............
E ;9. m
.....*............o...
1 ( . j . . . . .
* =
o * *
- a .
- r. . . . . . . . .
l o g. l .... . . . . . . ............. .......... .
-= . . . . .
j t . .
, .i
- s. .,
I . . C3 .
; C3, . .
............a..........................>.............
- o. .. ....... ...........>.......... . .
, 1 o .
. . . I
. . . . . . . l t . .
C3 . . .
. . . . \
O, . . . . . . .
, t 9968 '
l'972 1'976 l'980 1'9 884 l'988 l'992 l'996 TERRS I i I i
-126-l 1
1 1 i SIC 39 o
- 9 MISCELLANEOUS MANUFACTURING o...........
o
= .
- o. .
o,. ............ ...................... . ........................ ........ . . . . . . . . . . . . . . ..
. . . . . . . 1 , o . . . . . . .
4 . . . c,. . . . . . . .
- o. .
c, . . . . . . . C3 * . .
- o .
e ............ ...................... O
,o .
o .
- o . . . . . . .
~,,. . . . . . . . . . . . . ............. .......... . . . . . . . . . . . . ........ .... .
n3c . ro . 1o . E d. ............c............s...........
.*............a.............*.......
. o . o ............. .................... . 1 . l . . . . . . . o . . . . . . .
- o. - - '
. HISTORICAL- ! o.
g m . , . . l l FORECAST : l l t o 936't . . . . . . . o k- L _ _ _ _ _ _ _ _ a_ 3 9968 1972 1976 1980 1984 1988 1992 1996 TERRS
\
-127-
d
- 9) "r o
%'2
////
#4
%,)5$>q))}t@ > %;'$,
\ IMAGE EVALUATION NNNN i
TEST TARGET (MT-3)
- 1.0 5RM EA
- Fas"3 p-I.I b U2 ll]l2.0 t
i 1.8 ll 1.25 IA 1.6 4 6" = MICROCOPY RESOLUTION TEST CHART sr +/i a sp d! hh$/' ,
# /h n' -
,vfs, n h.g e 4, ggf
' ~ ~ ~ ^
o - 7_ ..
aft
<0)
@?b'
( Y //,,j//' hQ
$'S
. Nv'
)\Q)* IMAGE EVALUATION
'+ dis .%
i TEST TARGET (MT-3) i l l 1.0 $ Ett 120 y$llLM 1 1.l ;
'2 NE l.8 i l.25 1.4 1.6
- 6" >
MICROCOPY RESOLUTION TEST CHART A sr //
+ +(//s' 4:#;/>f+i/4xxxx s
i y, 44 A-is e s., a/A y _ _ __ h #' M 6[(O'(((b,p g
#5 *
*
- ed .e s
i OTHI3t CLASSES
- e i
A l l 1 I i e e O
- l l
, I o ,,
i l l 1 OTHER CLASSES ! Streetlighting Energy sales for streetlighting, which represent approxtmately 1.3% of the total Boston Edison Territory Sales, have increased at an annual rate of 4.5% per year for the 9-year period 1970 through 1979. With the installation of 275 kW of streetlighting demand in 1980 followed by 829 kW in 1981, 721 kW in 1982, 671 kW in 1983, 739 kW in 1984 and 790 kW in 1985, energy sales are
- cxpected to increase at a compound annual growth of 1.7% from 1979 to 1989.
Although the recent growth rate has been well over 4% and the rise of street-
! lights as an expected aid in crime prevention would appear to insure a con-tinuation of high growth rates, the increasing effictetcies in streetlighting ; tcchnology should moderate growth rates to the present astimates. The forecast io shown in Table E-6.
Railway i The railway classification represents approximately 0.3% of Boston Edison Territory Sales. Currently only sales to the Massachusetts Bay Transportation l Authority under a special contract are included in this sector. The remaining MBTA accounts are billed at commercial rates and are included in the commercial i cector. Total sales for this sector were 33,484 MWH in 1979. For the forecast pariod, sales are expected to remain approximately the same as 1979 in 1980, ! remain constant until 1983 at 52,960 HRH's per year and af ter 1983 assume 100% j of the MBTA requirements are supplied by BECo. The electrification of AMTRAK 4 io expecte,d to require the Company to begin supplying electric requirements in 1984, as supplied by AMTRAK engineering consultants. The railroad consumptioa j in expected to increase from 21 GWR (actual) in 1979 to 224 GWH's in 1989, Seles for Resale: Total Requirements Total requirements for resale classification is for municipal utilities purchasing their entire requirements from the Boston Edison Company and dis-tributing the energy to customers at retail. There are presently three munic-ipals which purchase their total requirements from Boston Edison Company. They cre Concord, Norwood and Wellesley. The requirements af each town are analyzed ] caparately and then combined to furnish projected total energy sales figures for this classification. In order to accomplish this, the three municipals are required to submit their own forecasts of total energy and peak requirements to the Company. . Prior to the transfer to other utilities of some of the tctal requirements rcsale customers in 1972 and 1974, the annual energy sales of t,he total require-msucs for resale classification had increased from 1,592 gigawatthours in 1970 to 1,733 gigawatthours during 1972 and then declined to 743 gigawatthours during 1975. As of November 1.1976, the Town of Reading became a freestanding member of NEPOOL and ceased purchasing under Boston Edison's total requirements rate. The esticated energy requirements for the Tevn of Reading are now included in Sales for 3e.1 ale Partial Requirements. As a result, the annual energy sales of the total requirements for resale classification declined to 729 gigawatthours in 1976 and to 440 gigawatthours in 1977. ( 1 128 -
v
.s * ,e .e The annual energy sales to this class increased from 453 gigawatthours in .- 1978 to 460 gigaustehours in 1979, a growth of 1.6%. However, during the fore-cast period, Norwood may not remain a customer as of aid 1983. For this report, we assume Norwood will purchase 60% of their requirements in 1981 and 1982 from the Company. We further assume that during 1983 they will purchase 60% of their 1' requirements from the Company for the first six months only. After the first l six ranths of 1983 service to Norwood is assumed to terminate. Therefore, sales for resale are assumed to decline from 460 GWH in 1979 to 306 GWH in 1989. The forecast is shwon on Table E-7. If Norwood remains a customer energy sales to I this class would be 553 gigawatthours in 1989, a growth of 1.8% per year.
Erritorv Iosses and Company Use The combination of territory losses and Company use can be calculated as 9.9% of territorial sales for the year 1979. While this percentage has fluctuated from 8.5% in 1971 to 10.6% in 1976, the figure of 8.8% represents the most recent loss study conducted within the Company. The forecast is shown below and in Table E-7.
- Territory losses and % Losses and Territory Year Sales Company Use Company Use Output 1980 9,579 843 8.8 10,422 1981 9,759 859 8.8 10,618 1982 - 10,037 883 8.8 10,920 1983 10,202 898 8.8 11,099 1984 10,410 916 8.8 11,326 1985 10,667 939 8.8 11,606 1986 10,863 956 8.8 11,819 1987 11,096 976 8.8 12,072 1988 11,377 1,001 8.8 12,379
~
1;o9 11,624 1,023 8.8 11,647 1990 11,916 1,049 8.8 12,964 k a l i a ) I
- 129 -
y-
* *& ,e BECo. Price Forecast The forecast of the averagc price of electcicity far territory energy sales is basically treated as a forecast of base price and fuel price. T*-
base price is produced from the base revenue torecast as.ociated with a fore-f cast of kilowatthours adjusted for revenue deficiencies. Revenue deficimacies are derived by determining whether the allowed race of' return is being reached
~
af ter operation and maintenance expenses, municipal taxes, etc. are subtracted from the base revenue forecast. These revenue deficiencies are then added to the base revenue forecast as rate increases in the appropriate years. The fuel price is developed by simulating what generating units are expected to produce !! (in accordance with a forecast of kilowatthours) and how much it is going to cost. The price of oil is based on the February 1980 ADL fuel forecast. I The real price of electricity is expected to grow f rom 5.41 cents per kilo-watthour in 1979 to 5.99 cents per kilowatthour in 1989, a compound mnual growth
- of 12. The forecast of real electric price is shown below.
i . Ecston Edison Company
, - Real' Price of Electricity l'
1979-1989 1 Price Year c/kWH 2 Growth 1979 5.41 1980 5.96 +10.2 1981 6.10 + 2.4 1982 5.82 - 4.6 1983 6.12 + 5.2
, 1984 6.24 --
+ 2.0 1985 6.10 - 2.2
] lg , 1986 6.53 + 7.1 1987 6.36 - 2.6 1988 6.02 - 5.4 I 1989 5.99 - 0.5 4< i.
*1978 is the base year
- 130 -
l l 1
w< 1 e .r .. a OTHER FACTORS i j i New Technology
, , For the purpose of this forecast we examined the feasibility of several nea f developments and their impact on the forecast. Of those investigated, electric
~
vehicles, inkjet printers, efficient motors and motor controllers are included in
- the forecast. For the purpose of this forecast, it was assumed that by 1989, j 5,260 electric vehicles will be garaged within the BECo. service territory. The annual energy use of these vehicles will be 21,040 megawatthours. Inkjet printers f do not have a major impact on the forecast, but have been included just the same.
l 1 When research1ag inkjet printers, it was found that the energy consumption is 1 1 approximately 60% lower than a comparable impact printer. The population of i , l~ inkjet prir.ters is expected to grow from 50 units in 1980 to 89 units in 1989. '{l ' The reduction in 1989 from inkjet printers is 12.112 kilowatthours. Ef fic i.ent ! motors are expected to reduce the forecast by 6 megawatthours in 1980 and 48 megawatthours in 1989. i I Alternate Energies ] Cogeneration's impact was re-estimated for the purpose of this forecast. It is f assumed that only nineteen of our industrial customers can potentially cogenerate. i If all nineteen were to cogenerate by 1989, the industrial forecast vill be reduced I by 195 megawatthours. Mandated conservation remains the same as in last year's \ for ecast. The overall reduction in the forecast in 1989 will be 134 gigawatthours. l 4; Solar heating and solar water heating have been re-estimated for the purpose of the forecast. In total solar heat will reduce the residential forecast by 5,047
- i. megawatthours in 1989.
1 t 4
- 130A -
O ' es ,e t 4 k i PEAK FORECAST P i 1 i s l 1 f I
~
1 1 1 l .I k e 1 - 1 1
o *.
' PEAK LOAD FORECAST (Territory Only) l 1 Historically. utilities have derived peak-loads by applying load factors to forecasted outaut energy. The strength of this methodology lay in the fact l that the annual load factor was extremely stable and moved only sluggishly i
! along a trend line; a change of one percentage point in ten years would be con-l sidered extremely volatile. The validity of the methodology resided in the accuracy of the results achieved. This is still one of the best methodologies ,
'.f one can reasonably predict values of the load factor. However, an av==ina- j l j
- r.isn of load duration curves since 1970 indicates that the annual load factor j u showing a marked decline. Therefore, it was necessary to develop a series ;
i l - ! peak factors which when applied to the annual usage of any sector would yield l < hat sector's contribution to sumer or winter peak. The derivation of these
- jeak factors is explained in the following section.
The off.sces of long-run and short-run price elasticity are included in the sector energy forecasts and are, therefore, also included in the peak demand 1 forecasts. i i If we apply the peak factors shown in Table I to the energy forecasts for j the various sectors, we obtain the forecast shown in Table II. A forecast of load factors can be made by applying the forecasted demand to the actual forecasted energy output requirements. These results are also shown in Table III. The territory output is shown in Table E-8. To find the 4 load factor the following equation is utilized. i I - 1 i Load Factor = Territorv Output (Energy) _ , Peak Load
- 24 hours
- 365 days 1 1
i
!- j 1
j i i ) t 1
\ I
- 131 -
e *. f 1 PEAK FACTORS
- Table I exhibits peak factors employed in the sunumer and winter peak demand forecasting methodology. As the footnote in the table indicates, a
, l peak factor is the ratio of a class of customers' demand at the time of the t Company system deak divided by the annual class energy. The peak factors for the summer of 1978 and for the winter of 1977 were developed at Edison using
( the Demand Allocation Program. They were projected into ths future at a con-stant value for all classes with the exception of the railroads sector. In
) that case, since it is expected that by 1984, r ae Company will be supplying AMIRAK load and the MBTA's total requirements ~ .ae peak factors were recalcu-lated using load data supplied by AMIRAK and W MBTA. The remaining peak factors in Table I (those prior to the summer of 1978 and the winter of 1977) came from Gilbert Associates, Ten Year Forecast of Electric System Demand and Energy Requirements, December, 1976.
Since the peak factors were developed with the Demand Allocation Program, it is appropriate to breifly review the program's function. The program was j purchased from Gilbert Associates as part of the Company's emerging load re-4 i search program. The program is a computerized model which has the capability of accepting load research data, bill frequency and loss parameters and produce 1 I customer class demands coincident with system peak. The program was initially I developed to expedite load research programa. However, when reasonable geo-graphic and/or seasonal correlations can be made with utilities possessing load research data, then this data can be applied to almost any utility's own monthly bill frequency parameters. In fact, this was the procedure followed to produce the above referenced peak factors. Gilbert Associates supplied the, pertinent-load research data and it was used with specific bill frequency data to produce class demands coincident with system peak. There are two methods of checking the peak load developed in this manner i (1) the resulting load factors whould be reasonable and (2) a separate peak load forecast con be made us'ng a load factor approach to act as a rough check. j 4 i However, it shotid be noted sat the load factor calculated for 1979 is un-adjusted for wea'her. The y ak of 2002 occurred at 910 when normally it would j be expected to occur at 960 When adjusted for weather, the peak would be j 2070 megawatts and the corrected load factor 57.8%. The degradation of the load factor has slowed recently and expected railroad sales to the MBTA would be pri-marily off-peak so that we would expect only a small change in the present load factor of 57.8%. As a rough check, the 57.8% load factor would give a peak of
, 2498 megawatts in 1989. This is in fairly good agreement with the actual fore- ; cast of 2543 megawatts. The forecasted peaks assume discontinuance of the jj i
650-780 temperature standards. 1 1 l 1 L e
- 132 -
o*.. . i o TABLE I
~
( <
. PEAK FACTORS
- c Street
[ Resales I.inhting Industrial _ Railroads __ Year Residential Comunercial _ W S W W V S V S V S .208 .152 .363 1 S
.244 .253 .176 .155 .156 .II9 .140 1975 .268 l .208 .192 .302
.195 .157 .116 .140
.263 .248 .204 .176 1976
.138 .208 .197 .319
.168 .195 .154 .119 1977 .262 .280 .204
.138 .203 .197 .311
.168 .226 .154 .131 1978 .194 .280 .237
.138 .203 .197 .319
.168 .226 .154 .131 1979 .194 .280 .237
.138 .203 .197 .319
.168 .226 .154 .131 1980 .194 .280 .237
.138 .203 .197 .319 l .168 .226 .154 .131 1981 .194 .280 .237
.133 .203 .197 .319
.168 .226 .154 .131 f
i 1982 .194 .280 .237
.203 .197 .319
.168 .226 .15 4 .111 .138 1983 .194 .280 .237
.185 .203 .197 .319
.168 .226 .154 .111 1984 .194 .280 .237 3
.185 .203 .197 .319
.168 .226 .15 4 .111 1985 .194 '.280 .237
.185 .203 .197 .319
.168 .226 .154 .111
! 1986 .194 .280 .237
.185 .203 .197 .319
.168 .226 .154 .111 1987 .194 .280 .237 .
.185 .203 .197 .319
.168 .226 .154 .111
' 1988 .194 .280 .237
.183 .203 .197 .319
.168 .226 .154 .111 1989 .194 .280 .237
.203 .197 .319
.237 .168 .226 .154 .111 - .185 1990 .194 .280 '
l l l *This is the ratio of class peak coincident with system peak to annual class I 4, energy (gigawatthours). b (
- 133 -
.- - . . .- - . _ - _ . - _ - . _ . .~ . . .
' ' ~ ~ ~ ~ ~ ---- -- n ... -_ _ __ _
i
. }
TAat.E 11_ 80ST.41 EDISOD OMEPANY g. PEAK DU AND FORF'.AST 1980-1989 I 8attroad S-5 Total
- mesidential Comunercial _ Indust r ial _ street gghtsna .
Suasser Winter Summer 2 Wint er }__
, Summer Winter WJ ter Summer Winter Year h _eg., ytett e,tt h-e t glat_e.E
- 5 95 92 2.091 +4.45 1.904 +5.02 .
778 194 269 40 4 1980 499 721 1.098 7 88 85 2.130 41.87 1.936 +1.68 802 '.00 .? 7 3 41 7 198: 504 728 1.131 7 81 79 2.193 +2.96 1.989 +2.74 480 !!79 42 7 1964 516 745 1.140 836 69 67 2.233 +1.82 2.016 + 1. 36 231 42 6 7 1983 518 748 1.225 868 415 10 17 57 55 2.277 +1.97 2.054 +1.48 755 896 422 288 43 1984 523 1.264 22 58 56 2.332 +2.42 2.104 +2.43 922 428 292 44 13 1985 532 768 1.301
+1.80 2.137 +1.57 !
434 296 45 16 27 59 57 2.374 l 1986 531 766 1.334 946 19 32 60 38 2.424 +2.11 2.181 +2.06 964 444 302 46 1987 540 780 1.360 22 37 61 59 2.482 +2.39 2.236 +2.52 984 458 312 47 8 1988 553 797 1.388 e 47 25 41 62 60 2.53' +2.10 2.282 st2.06 473 $ 1989 560 809 1.413 1.002 322 61 2,596 +2.45 2.336 +2.37 330 48 28 46 63 8 1990 569 821 1.452 1.030 484
- Columns may not add to totale due to roundina. ,
i
='.. .s TABLE III BOSTON EDISON COMPANY ,. BECo. 'iERRITORY SUMMER PEAK FORECAST (Megawatt.s) ,
ii l I' April 1, 1979 April 1, 1980 t l Year Forecast Forecast Load Factor ; ! ,. 1979 2,094 2,002(Actual) 59.7 ! 1980 2,101 2,091 56.9 1981 2,157 2,130 56.9 l 1982 2,239 2,193 56.8 1983 2,320 2,233 56.7 1984 2,355 2,277 56.8 1985 2,457 2,332 56.8 1986 2,596 2,374 56.8 1987 2,686 2,424 56.8 i
- 1988 2,728 2,482 56.9 f' 1989 2,878 2,534 57.0
- 1990 2,973 2,596 57.0 j Compound Annual Growth Rate 1979-1989 2.4%
I
! BECo. TERRITORY WINTER PEAK FORECAST (Megawatts)
April 1, 1979 April 1, 1980 Year Forecast Forecast l 1979 1,908 1,813(Actual) J
~
1980 1,912 1,904 ) l 1981 1,955 1,936 i j % 1982 2,016 1,989 i 1983 2,098 2,016 1984 2,126 2,054 ; 1985 2,208 2,104 l f 1986 2,318 2,137 1987 2,386 2,181 1988 2,460 2,236 1 1989 2,535 2,282 1990 2,608 2,336 , Compound Annual Growth 1979-1989 +2.6' l
- 135 -
et ,
- EFSC TABLES 8 .
3 f e
TABLE E-1 Company: BOSTON EDISON COMPANY
aso EFSC (2/76) Filing Date: April 1, 1980 For Years ending on: December 31, 1980 RESIDENTIAL CLASS CONSUMPTION f CUSTOMERS WITH ELECTRIC HEATING i
. Total Annual Average Use Annual Consumption Annual Change Per Customer Change MWh Change Yer Customers % kWh % (000 amitted) %
.ictorical:
~970 10,090 21,811 219.0
'A971 11,514 +14.7 22,176 + 1.7 255.3 +16.6 972 13,445 +16.8 22,437 + 1.2 301.7 +18.2 1973 14,821 +10.2 21,710 - 3.2 321.8 + 6.7 f
16,122 + 8.8 22,743 + 4. 8 366.7 +14.0 l974 1.975 17,531 + 8.7 19,709 -13.3 345.6 - 5.8 f-18,903 + 7.8 20,890 + 6.0 394.9 +14.7 976
'977 23,095 +22.2 18,165 -13.0 419.5 + 6.2 25,917 +12.2 18,856 + 3.8 488.7 +16.5 5978 .
.979 26,994 + 4.2 16,652 -11.7 449.5 - 0.8 Forecast:
.980 28,516 + 5.6 13,525 -18.8 385.7 -14.2 1981 30,120 + 5.6 13,382 - 1.1 403.1 + 4.5 t982 31,645 + 5.1 13,253 - 1.0 419.4 + 4.0 33,110 + 4.6 13,144 - 0.8 435.2 + 3.8
, 1,983 1984 34,530 + 4.3 13,192 + 0.4 455.5 + 4.7
!985 35,9_- + 4.0 12,936 - 1.9 464.7 + 2.0 37,187 + 3.5 12,927 - 0.07 480.7 + 3.4 1986 1987 38,447 + 3,4 12,884 - 0.3 495.3 + 3.0 1988 39,682 + 3.2 - 12,843 - 0.3 509.6 + 2.9 1989 40,905 + 3.1 12,834 - 0.7 525.0 + 3.0 1990 42,115 + 3.0 12,820 - 0.1 540.0 + 2.9
-136-
TABLE E-2 Company: BOSTON EDISON COMPANY
.cca IFSC (2/76) Filing Date: April 1, 1980 For Years ending on: December 31, 1980 RESIDENTIAL CLASS CONSUMPTION CUSTCHERS WIMOUT ELECTRIC HEATING Total Annual Average Use Annual Consumption Annual Change Per. Customer Change MWh Change . Yer Customers % kWh % (000 On;ttted) %
lictorical:
'.970 450,940 4,280 1,930.2 1971 448,376 -0.6 4,512 +5.4 2,022.9 +4.8
{972 454,668 +1.4 4,592 +1.8 2,087.8 +3.2 1973 459,910 +1.0 4,789 +4.3 2,022.7 -3.1
.974 462,544 +0.6 4,406 -8.0 2,038.0 +7.6 A
1975 462,396 -0.03 4,533 +2.9 2,096.0 +2.8 4
'.976 460,109 -0.5 4,551 +0.4 2,094.0 -1.0
'.977 455,638 - 1. 0 4,651 +2.2 2,119.2 +1.2 1978 456,140 . +0.1 4,628 -0.5 2,111.0 -0.4 j .979 459,374 +0.7 4,676 +1.0 2,147.9 +1.7 i Forecast:
I
.980 465,461 +1.3 4,702 +0.6 2,188.5 +1.9
] 1981 471,876 +1.4 4,654 - 1. 0 2,196.2 +0.4
.982 477,978 +1.3 4,693 +0.8 -
2,242.8 +2.1 i 1983 483,840 +1.2 4,621 -1. 5 2,235.6 -0.3 1984 489,516 +1.2 4,575 -1.0 2,239.7 +0.2
.985 495,089 +1.1 4,600 +0.5 2,277.6 +1.7 1986- 500,141 +1.0 4,509 -2.0 2,255.1 -1.0
.987 505,1.* ' +1.0 4,530 +0.5 2,288.4 +1.5 1988 510,078 +1.0 - ,,585 +1.2 2,338.6 +2. 2
.989 514,966 +1.0 4,588 +0.06 2,362.7 +1.0 l 1990 519,806 +0.9 4,603 +0.3 2,392.7 +1.3
-137-
, ..-4 - -
6.a .. TABLE F,-2A Company: BOSTON EDISON COMPANY Mass EFSC (2/76) Filing Date: April 1, 1980 For Years Ending On: December 31, 1989 j . - - RESCENTIAL CLASS CONSUMPTION
- TOTALS Total Annual Average Use Annual Consumption Annual Change Per Customer Change __
MWh Change Year Customers % kWh % (000 omitted) % r j Historical: 1970 460,980, 4,662 2,149.2 1971 459,890 -0.2 4,954 +6.3 2,278.2 +6.0 1972 468,113 +1.8 5,105 +3.0 2,389.5 +4.9 1973 474,731 +1.4 5,318 +4.2 2,524.4 +5.6
~
1974 478,666 +0.8 5,024 -5.5 2,404.7 -4.7 1975 479,927 +0.3 5,088 +1. 3 2,441.7 +1.5 1976 479,012 -0.2 5,195 +2.1 2,448.7 +0.3 1977 '478,733 -0.06 5,303 +2.1 2,538.8 +3.7 1978 482,057 +0.7 5,310 +0.3 2,559.7 +0.8
- 1979 486,368 +0.9 5,340 +0.6 2,597.4 +1.5 Forecast:
1980 493,977 +1.6 5,210 -2.4 2,574.2 -0.9 i 1981 501,996 +1.6 5,178 -0.6 2,599.3 +1.0 1982 509,623 +1.5 5,220 +0.8 2,662.2 +2.4
-1983 516,950 +1.4 5,166 -1. 0 2,670.8 +0.3
[, 1984 524,048 +1.4 5,144 -0.6 2,695.2 +0.9 1985 531,012 +1. 3 5,164 +0.4 2,742.3 +1.7 2,735.8 1986 537,328 +1.2 5,095 -1. 3 -0.2
~
1987 543,578 +1.2 5,117 +0.4 2,783.7 +1.8 1988 549,760 +1.1 5, 17 9 +1.2 2,848.2 +2.3 1989 555,871 +1.1 5,194 +0.3 2,887.7 +1.4 1990 561,921 +1.1 5,218 +0.5 2,932.7 +1.6
- 138 -
TABLE E-3 Compay: BOSTON EDISON COMPANT
, Mass EFSC (2/76) Tiling Date: April 1, 1980 For Yearu Encing On: December 31, 1989 i
COMMERCIAL CLASS CONSUMPTION Co m cial Consumption Annual MWh Change Year (000 Omitted) % Historical: 1970 2,894 + 9.5 1971 3, 136 + 8.4 1972 3, 34 6 + 6.7 1973 3,756 +12.2 I 1974 3,691 - 1.3 i 1975 3,924 + 6.3 9 ' 1976 4,144 + 5.6 1977 4,277 + 3.2 1978 4,428 + 3.5 1979 4,550 + 2.8 l Forecast: 1980 4,633 + 1.8 1981 4,772 + 3.0 1982 4,978 __
+ 4.3 3
1983 5,169 + 3.8 1984 5,335 + 3.2 1985 5,488 + 2.9 i 1986 5,629 + 2.6 1987 5,737 + 1.9 f L 1988 - 5,857 + 2.1 1989 5, 96 4 + 1.8 1990 6,128 + 2.7 i I
- 139 -
h.
. s Company 4GSToll th! SON QMFANY TABLE E-4 Mass ErsC (2/76) F111n8 Dats: April 1, 1980 ,
INDUST 8IAL CiASS: CONSL89 TION BT 1W-DICIT Sic Cute Beductions MeSawattinours Due to Coseneration [ (000 Omitted) 6 Mandated ( 38 ) conservattaa, Y+sr ( 20 ) ( 22 ) ( 26 ) ( 27 ) ( 28 ) ( 30 ) ( 32 ) ( 33 ) ( 34 ) ( 35 ) ( 36 ) ( 37 ) ( 39 ) other Totala Elztorical , 29 115 118 521 89 2M 9 44 - 1,813 1973 165 24 103 92 124 108 17 35 83 128 494 123 278 10 52 - 1,860 1971 189 24 116 84 133 99 12 29 72 148 505 124 295 12 54 - 1,939 91 141 99 13 1972 194 ' 26 132 25 28 76 152 471 118 309 65 55 - 2,026 1973 246 20 129 90 140 101 90 25 23 67 136 394 61 269 45 51 - 1,753 1974 226 17 ,125 84 135 27 24 60 161 409 61 257 10 45 - 1,679 1775 229 16 100 84 125 71 20 21 65 178 391 68 200 8 46 - 1,739 1976 246 19 105 87 127 78 22 18 56 188 406 87 288 8 45 - 1,759 1977 248 20 118 88 92 75 22 18 54 194 412 96 300 8 41 - 1,728 1978 286 27 116 84 63 75 64 78 23 17 55 194 424 96 311 9 44 - 1,758 1979 215 26 118 84 Frrtcasts
~
27 120 86 38 80 23 16 54 209 437 69 323 9 46 - 9 1,745 1980 217 38 83 23 16 56 216 450 78 3M 9 44 - 33 1,772
!!88 218 28 122 80 90 38 86 23 16 57 226 469 85 348 9 47 - 56 1,813 1982 221 28 126 220 29 129 93 38 Sd 24 16 57 233 485 85 363 9 46 - 81 1,835 1983 96 38 93 24 16 58 239 503 85 379 10 50 -105 ~1 ,869 1984 221 30 132 99 38 % 25 16 58 244 519 92 395 10 47 -131 1,994 1985 221 30 135 222 31 138 102 38 100 25 16 59 250 537 92 412 to 47 -158 1,921 1986 225 32 143 106 38 105 26 16 60 257 559 92 432 to 47 -189 1,964 1987 1988 229 34 149 Ill 38 111 28 17 61 265 588 92 458 !! 47 -212 2,027 116 38 114 29 17 62 274 616 92 446 11 47 -240 2,093 1989 235 35 156 121 38 125 30 17 63 282 641 92 510 12 48 -268 2,142 1990 232 37 162 8 1he rows may not add enactly to the total due to roundin8
- 140 -
'.> .. \
l I TABLE E-5 Company: BOSTON EDISON COMPANY j Mass EFSC (2/76) Filing Date: April 1, 1980 Joe Years Ending On: December 31, 1989 j
*- INDUSTRIAL CLASS CONSUMPTION i
Industrial Annual Consumption , t MWh Change j Year (000 Omitted) % ! l c Historical: 1970 1,813 + 1.1 1971 1,860 + 2.6 I 1972 1,939 + 4.2 i 1 1973 2,026 + 4.4 1 l
! 1974 1,753 -13.4 l }
1975 . 1,679 - 4.2 1976 1,739 + 3.6 1977 1,759 + 1.2 , 1978 1,728 - 1.8 ;
\ , 1979 1,758 + 1.7 l l
Forecast: 1980 1,745 - .7 1981 1,772 + 1.6 1982 1,813
+ 2.3 1983 1,835 + 1.2 l
+ 1.9 1
1984 1,869 1985 1,894 + 1.3 ,
- h. . l 1986 1,921 + 1.4 1,964 + 2.2 i 1987
, 1988 2,027 + 3.2 l
1989 2,093 + 3.2 l l 1990 2,142 + 2.3 l l c. l
- 141 -
N .. TABLE E-6 Company: BOSTON EDISON COMPANY
, Mass EFSC (2/76) Filing Date: April 1, 1980 For Years er ding on: December 31, 1989 STREETLIGHTING CLASS CONSUMPTION r' RAILROAD CLASS CONSUMPTION Streetlighting Railroad Constamption Annual Consumption Annual MWh Change MWh Change Year (000 Omitted) % (000 Omitted) %
< Historical: , 1970 84 +2.5 19 +36.6 1971 87 +3.6 24 +26.3 1972 91 +4.6 22 - 8.4 i 1973 98 +7.7 25 +13.6 1974 100 +2.0 26 + 4.0 , 1975 106 +6.0 23 -11.5 g 1976 108 +1.9 17 -26.1 }~ 116 +7.4 21 +23.5 1977 1978 121 +4.3 21 0.0 1979 125 +3.3 21 0.0 Forecast: a. 1980 126 +0.8 33 +57.1 1981 129 +2.4 53 +60.6 i
- 1982 131 +1.6 53 0.0 I --
0.0 1983 133 +1.5 53 1984 136 +2.3 94 +77.4 l 1 1985 138 +1.5 118 +25.5 1986 141 +. 2 146 +23.7 1987 143 +1.4 172 +17.8 f 1988 146 +2.1 198 +15.1 1989 148 +1.4 224 +13.1 1990 151 +2.0 251 +12.0 k=
- 142 -
TABLE E-7 Company: BOSTON EDISON OMPANY Mass EFSC (2/76) Filing Date: April 1, 1980 For Years ending on: December 31, 1989 SALES FOR RESALE LOSSES AND INTERNAL USE MWh (000 Omitted) (. Sales for Resale Annual Territory Annual , Total Requirements Chan,;e Losses and Change Year Customers % Internal Use % Historical: 1970 1,592 749 + 0.8 1971 1,697 + 6.6 770 + 2.8 i 1972 1,733 + 2.1 878 +14.0 1973 1,205 -30.5 867 - 1.3 1974 1,053 -12.6 872 + 0.6 1975 743 -29.4 888 + 1.8 1976 729 - 1.9 982 +10.6 1977 440 -39.6 943 - 4.0 1978 453 + 3.0 961 + 1.9 1979 460 + 1. 6 951 - 1.0 Forecast: 1980 468 + 1.7 843 -11.4 1981 434 - 7.3 859 + 1.9 i - 1982 400 - 7.8 883 + 2.8 , 1983 340 - 15. 0 897 + 1.6 1984 281 -17.4 916 + 2.1 I 1985 286 + 1. 8 939 + 2.5 l j 1986 291 + 1. 8 956 + 1.8 ( 1987 296 -
+ 1.7 976 + 2.1 1988 301 + 1.7 1001 + 2.6 i
1989 306 + 1.7 1023 + 2.2 , 1990 312 + 2.0 1049 + 2.5
- 143 -
l
-_~
- - - r- - - - _ . _ , _ _. .. _- ,
TABLE E-8 Campxy; DOStoll EDisoll C0ftPANY Filing cate: April I, 1980 thas EFsc (2/76) For Years Ending On December 31, 1989 TOTAL EhENCY OUTPUT REQUIREf1ENTS g Iman (000 Oisitted) , Sesidential Nesidential Estes for Territory Territory
- With With ut Resale Total
- Asamal Lasses & Emer8y Aamuel Electric Electric Street Total Territorist m ete Internal output Chtsee ,
Veer Weatina lleatina Commercial Industrial Llahtina Railroad Reentrements Sales 1 Use Seemisements 1 , 116 st orical: 1970 219 3,930 2,894 1,813 84 19 1,592 , 8,552 +7.4 749 9,302 +6.9 1978 255 2,023 3,136 I,860 87 24 3,697 9,083 +6.2 770 9.852 +5.9 1972 3a2 2,088 3,346 3,939 98 22 8,733 9,520 +4.8 878 18,398 +5.5 1973 322 2 ,142 3 3,756 2,026 98 25 1,205 9,634 +1.2 867 10,508 +3.0 1974 367 2,034 3,692 8.753 100 26 1.053 9,028 -6.3 872 9,900 -5.7 1975 346 2,096 3,924 1,679 106 23 743 8,938 -1.2 SSS 9,804 -3.0 1976 395 2,094 4,144 3,739 108 17 729 9.226 +3.5 982 10,208 +4.1 1977 420 2,119 4,277 1,759 116 28 440 9.15l '- 0.8 943 10.093 . -l.1 1978 489 2,Ill 4,357 1,728 121 21 453 9,3tl *1.7 968 10,272 +1.4 450 4,550 1,758 125 28 460 9,524 +2.3 951 10.475 +2.0 1 1979 2.848 7 Forecasts
+0.6 10,423 1980 475 2,100 4.633 1,745 126 33 468 9,579 843 -0.5 ' 1988 538 2,06l 4,772 I,772 129 53 434 9.759 +1.9 859 10,618 +1.9 1982 564 2,098 4,978 1,813 131 53 400 10,037 +2.8 883 10,920 +2.4 1983 573 2,098 5,169 1,835 133 53 340 10,202 +l.6 897 11.099 +1.6 1984 593 2,102 5.335 1,869 116 94 281 10,410 +2.0 986 18,326 +2.0 1985 594 2,148 5.488 8.894 338 118 286 10,667 +2.5 939 II,606 +2.5 1986 615 2,828 5,629 1,928 I48 346 298 10,863 +1.8 956 II,819 +1.8 1987 636 2,144 I,96 143 172 296 11.096 +2.5 976 12,072 +2.8 5,737g 1988 661 2,187 5,857 2,027 146 198 303 II,377 +2.5 t,001 12,379 +2.5 1989 681 2,207 5,964 2,093 J48 224 306 11,624 +2.2 I,023 12,647 +2.2 1990 702 2,231 6,828 2,842 til 25I 382 II,916 +2.5 1,041 12,964 +2.5
- Sows may not add to totals due to rounding. '
N. .. TABLE E-8A TOTAL SYSTEM ENERGY OUTPUT REQUIREMENTS Mass EFSC (2/76) MWH (ooo omitted) Territory Sales for System Energy Resale Annual Energy Annual
, Output Partial Change Output Change ; Year Requirements Requirements % Requirements %
t ; Historical: 1970 9302 1317 - 2.3 10,617 - 5.6
, 1971 9852 769 - 41.6 10,622 + 0.1 l l
1972 10398 386 - 49.8 10,784 + 1.5 1973 10501 1669 +422.4 12,170 + 12.9 1974 9900 1269 - 24.0 11,169 - 8.2
- 1975 9804 1417 + 11.7 11,222 + 0.5 1976 10208 1503 + 6.1 11,711 + 4.4 l
1977 10093 1705 + 13.4 11,798 + 0.7 I 1978 10272 2316 + 35.8 12,589 + 6.7 2 1979 *10475 2632 + 13.6 13,107 - 4.1
, F'o recast:
1980 10423 1459 - 44.6 11,882 - 9.3
- 1981 10618 1949 + 33.6 12,567 + 5.8 1982 10920 2331 + 19.6 13,'251 + 5.4
~
1983 11099 2064 - 11.5 13,163 - 0.1 1984 11326 1965 - 4.7 13,294 + 1.0 1985 11606 1665 - 15.4 13,271 + 0.8 1986 11819 1437 - 13.7 13,256 - 0.1 1987 12072 1404 - 2.3 13,476 + 1.7 1988 12379 1258 - 10.4 13,637 + 1.2
~
! 1989 12647 1114 - 11.4 13,761 + 0.9 1990 12964
.+
- 145 -
46 .e , Company: BOSTON EDISON COMPANY TABLE E-11 Mass ETSC (2/76) Filing Date: April 1, 1980 For Years Ending On: December 31, 1989 '~ TOTAL SYSTEM 10AD ' BOSTON EDISON TERRITORY Territory Winter Summer { Annual Peak Annual Peak Annual Annual Output Load Change Load Change Load Mvh Change MW MW % Fa::cor Year (000 Omitted) % Historical: 60.9 9,302 +6.9 1738 +5.1 1744 +6.9 1970 9,852 +5.9 1791 +3.0 1877 +7.6 59.9 , 1971 ;
+5.5 1818 +1.5 1912 +1.9 62.1 1972 10,398 10,501 +1.0 1683 -7.5 2030 +6.2 59.1 1973 j '
9,900 -5.7 1660 - 1. 4 1891 -6.8 59.7 1974 9,804 -1.0 1756 + 5. 8 1933 +2.2 57.9 1975 9,906 +1.0 1792 +2.1 1970 +1.9 59.4 1976 10,093 +1.9 1828 -0.3 2013 +2.2 57.9 1977 4 10,272 +1.8 1825 -0.2 2031 +0.6 57.7 1978 10,475 +2.0 1813 -0.7 2002 -1.4 59.7 1979 Forecast: 10,423 -0.5 1904 +5.0 2091 +4.4 56.9 1980
+1.9 1936 +1.7 2130 +1.9 56.9 1981 10,618 10,920 +2.8 1989 +2.7 - 2193 +3.0 56.8 1982
+1.6 2016 +1.4 2233 +1.8 56.7 1983 11,099
+2.0 2054 +1.9 2277 +2.0 56.8 1984 11,326
+2.5 2104 +2.4 2332 +2.4 56.8 1985 11,606
+1.8 2137 +1.6 2374 +1.8 56.8 1986 11,819
+2.1 2181 +2.1 2424 +2.1 56.8 1987 12,072
+2.5 2236 +2.5 2482 +2.4 56.9 1988 12,379
+2.2 2282 +2.1 2534 +2.1 57.0 1989 12,647
+2.5 2336 +2.4 2596 +2.4 57.0 1990 12,964
- 146 -
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- 150 -
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- 151 -
1 i
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!'. ass C'SC (2/76) Tiling Date _ April 1, 1980 LOAD PROFII.E i .
Winter of (years) 1080/1990,_ ,, Winter Paak (MW) __'L282
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