ML20003F904
| ML20003F904 | |
| Person / Time | |
|---|---|
| Issue date: | 08/18/1980 |
| From: | Murley T NRC OFFICE OF NUCLEAR REGULATORY RESEARCH (RES) |
| To: | Harold Denton Office of Nuclear Reactor Regulation |
| References | |
| RIL-097, RIL-97, NUDOCS 8104230860 | |
| Download: ML20003F904 (4) | |
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MEMORANDUM FOR: Harold R. Denton, Director Office of Nuclear Reactor Regulation Thomas d. Murley, Acting Director FROM:
Office of Nuclear Regulatory Research
SUBJECT:
RESEARCH INFORMATION LETTER # 97 "AN ECONOMETRIC STUDY I
0F ELECTRICITY DEMAND BY MANUFACTURING INDUSTRIES" Introduction and Sumnary This memorandum transmits the results of completed research on electricity demand in the United States originating in the manufacturing sector of the It is part of a research pre; ram in support of NRC's effort to economy.
maintain an adequate capability to evaluate need for power, as required by the licensing process for nuclear power plants under the National Environmental Policy Act.
Demand frcm the manufacturing sector accounts for approxi-mately 38 percent of total electricity demand and is a relatively volatile component of total demand. An accurate forecasting model must include a detailed manufacturing sector. The research effort described here will be used in the develcpment of the SLED (State Level Electricity Demand) model used to assess forecasts of total electricity demand by state. The research was performed by Oak Ridge National Laboratories under the direction of the Environmental Effects Research Branch in response to a request from your office (NRR-77-01).
Methodolcqy A model of electricity demand was specified which contained two simultaneous equations.
One equation reflects the behavior of the firm with an assumed objective of cost minimization.
This results in an equation for each manufacturing firm of the type:
YJ = F (Q, P1, P2--, Pj) j=1, 2---J where Yj is the quantity demandcd of the jth input in production, Q is the output level of the finn, and PJ is the price of the jth input.
Since the production input of interest.is electricity, the derived demand for l
i electricity can be expressed as a function of final output of the firm, price of l';
electricity, and prices of other production inputs, including substitute fuels.
Sunning the equations over all firms in an industry yields an equation for that industry. The second equation incorporates electricity prices into the model, specifically the declining block-rate pricing structure in practice for most U.S. manufacturing industries.
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,f e Harold R. Denton industries at the SIC The equatiens were estimated for 15 U.S. manu ategory Tire series data on an representing all remaining ranufacturing industries.
1959-1976 were used in estication.
annual basis for the years Identification of the Manufacturing Industries Analyzed Electrical Consumption" in 1976 Table 1.
Percent of Total 12 10 kWH 100.0 Description 634.9 0.8 SIC Code Ali industries 5.2 Canned, cured, and frozen foods 1.0 6.1 0.7 203 Grain-mill products 4.2 0.6 204 Weaving mills, cotton 3.9 3.3 221 Knitting mills Paper mills, except building paper 20.9 1.6 225 10.2 262 Paperboard millsIndustrial chemicals, exclusive of 263 2SlA the Department of Energy's three 74.9 2.6 11.8 uranium enrichment plants 16.8 4.1 Plastic raterials and synthetics 26.3 252 Petroleum refining Glass and glassware; pressed or 1.0 291 6.5 1.4 322 bicwn 9.1 Cement, hydraulic Blast furnace and basic steel pro-8.6 324 54.6 1.8 331 ducts 11.4 10.5 Iron and steel foundries 66.8 2.8 332 Prirary nonferrous metals 17.7 47.3 333 Motor vehicles and equipment 300.2 371 Til remaining industries, Source:
consumed.
i aDoes not include the amount of self-generat 1976, Washington, D.
C.,.
June 1978.
h ranufacturi:
Results The results of estimating the system of equations for eac Coefficients for the price of electricity and d were statistically lite favorable.
i output were of the expected sign for all industr es an The results indicated that industry were t icity for the majority of significant at the 5 percent level for most.
l natural gas was a significant substitute for e ec rThe fo d
(percent change in demand caused by a 1 percent change icity demand caused by industries.
and value-added elasticity (percent change in electr a 1 percent change in final output less raw mater a code.
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.3 Harold R. Denton
( 3 Estimated short-run and long-run elasticities of demand for electricity Table 2.
Industry Own-price elasticities Value-added elasticities SIC code Snort run Long run Short run Long run 203
-1.46
-2.59 0.28 0.49 204
-0.23
-1.52 0.10 0.66 221
-0.13
-0.17 0.46 0.62 225
-1.00
-1.86 0.48 0.90 262
-0.86
-1.20 0.23 0.32 263
-0.21
-0.24 0.71 0.81 282
-0.58
-1.46 0.32 0.82 281A
-0.22
-0.40 0.43 0.79 291
-0.03
-0.19 0.18 1.03 322
-1.07
-1.29 0.21 0.25 324
-0.09
-0.11 0.82 1.02 331
-0.43
-0.95 0.39 0.85 332
-0.46
-2.01 0.38 1.61 333
-0.65
-1.02 0.60 0.94 371
-1.51
-1.66 0.46 0.51 Other
-0.89
-1.57 0.31 0.55 The model was used to forecast annual rates of change of electricity demand Where inputs of future levels of variables such as prices were through 1995.
needed, standard forecasts of the Department of Energy or other sources were For the manufacturing sector as a whole, electricity demand is fore-cast to increase at an average rate of 3.7 percent per year from 1977 to 1995, used.
1959-1974 scmewnat less than the 5.1 percent growth experienced during the period.
Table 3 gives growth rates for each manufacturing industry.
Forecasted average annual crowth rate of consumotion by industry Table 3.
Average annual growtn rate of demand (1977 to 1995)
Industry 3.7 SIC 203 3.8 SIC 204 3.3
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SIC 221 5.5 SIC 225 3.5 SIC 262 3.3 263 5.6
, 281 A 4.7 C 32 4 gC 0.8 IC 291 2.3 3ry ilC 322 4.1 on #8 SIC 324 5.8 SIC 331 6.9 SIC 332 2.7 N
SIC 333 2.2 SIC 371 2.8 Other Industries 3.7 All Industries
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C Harold R. Denton 4-Conclusions and Recocrnendations The results of the research will be incorporated into the SLED (State Level Electricity Demand) Model, and should lead to a significant enhancement in the capability of that modeling system to supply need for power forecasts.
This should be useful to your staff in their evaluations of need for power, as called for in the licensing process.
For further inforcation on this study, please contact Dr. Clark Prichard (427-4358).
Thomas E. Murle', A ting Director Office of Nuclea gulatory Research
Enclosure:
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