CHAPTER 13. UTILITY IMPACT ANALYSIS
 

TABLE OF CONTENTS
 

13.1 INTRODUCTION ............................................................................................................ 13­1
 

13.2 METHODOLOGY ........................................................................................................... 13­2
 

13.3 RESULTS ......................................................................................................................... 13­2
 

REFERENCES .......................................................................................................................... 13­3
 

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CHAPTER 13. UTILITY IMPACT ANALYSIS
 

13.1 INTRODUCTION
 

The U.S. Department of Energy (DOE) will analyze the effects of proposed beverage

vending machine energy conservation standards on the electric utility industry as part of the

Notice of Proposed Rulemaking analysis, using a variant of the Energy Information

Administration (EIA)’s National Energy Modeling System (NEMS).a The NEMS is a large,

multi­sectoral, partial equilibrium model of the U.S. energy sector. EIA uses NEMS to produce

the 2007 Annual Energy Outlook (AEO2007).

1 NEMS produces a widely recognized baseline

energy forecast for the United States through 2030, and this energy forecast is available in the

public domain. DOE will use a variant known as NEMS­BT to provide key inputs to the

analysis. The utility impact analysis will compare model results for the base case to policy cases

where proposed energy efficiency standards are in place. Using NEMS­BT for the utility

analysis offers several advantages. As the official DOE energy forecasting model, NEMS relies

on a set of assumptions that are transparent and have received wide exposure and commentary.

NEMS­BT allows an estimate of the interactions between the various energy supply and demand

sectors and the economy as a whole. The utility analysis will report changes in installed capacity

and generation, by fuel type, which would result for each trial energy efficiency standard level,

as well as changes in electricity sales to the commercial sector.

DOE conducts the utility analysis as a policy deviation from the AEO2007, by applying

the same basic set of assumptions. For example, the operating characteristics (e.g., energy

conversion efficiency, emissions rates) of future electricity generating plants are as specified in

the AEO2007 reference case, as are the prospects for natural gas supply. Also, DOE will explore

deviations from some of the reference case assumptions, to represent alternative futures. Two

alternative scenarios use the high and low economic growth cases of AEO2007. (The reference

case corresponds to medium growth.) The high economic growth case assumes higher projected

growth rates for population, labor force, and labor productivity, which would result in lower

predicted inflation and interest rates relative to the reference case and higher overall aggregate

economic growth. The opposite is true for the low growth case. Starting in 2012, the high

growth case predicts growth in per capita gross domestic product of 3.5 percent per year,

compared with 3.0 percent per year in the reference case and 2.5 percent per year in the low

growth case. While supply­side growth determinants are varied in these cases, AEO2007

assumes the same reference case energy prices for all three economic growth cases. Different

economic growth scenarios will affect the rate of growth of electricity demand.

a For more information on NEMS, please refer to the U.S. Department of Energy, Energy Information

Administration documentation. A useful summary is National Energy Modeling System: An Overview 2000,

DOE/EIA­0581(2000), March 2000. EIA approves use of the name NEMS to describe only an official version of

the model without any modification to the modeling code or data. Because this analysis entails some minor code

modifications and the model is run under various policy scenarios that are variations on EIA assumptions, DOE

refers to it by the name NEMS­BT (BT is DOE’s Building Technologies Program, under whose aegis this work has

been performed). NEMS­BT was previously called NEMS­BRS.

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13.2 METHODOLOGY

The electric utility industry analysis will consist of NEMS­BT forecasts for generation,

installed capacity, sales, and prices. The NEMS provides reference case load shapes for several

end uses. The model uses predicted growth in demand for each end use to project total electric

system load growth for each region, which it uses in turn to predict the necessary additions to

capacity. The NEMS­BT accounts for the implementation of energy efficiency standards by

decrementing the appropriate reference case load shape. DOE determines the size of the

decrement using data for the per­unit energy savings developed in the life­cycle cost and

payback period analysis (chapter 8) and the forecast of shipments developed for the national

impact analysis (chapter 9).

The predicted reduction in capacity additions is sensitive to the peak load impacts of the

standard. DOE will investigate the need to adjust the hourly load profiles that include this end

use in NEMS­BT. Since the AEO2007 version of NEMS forecasts only to the year 2030, DOE

must extrapolate the results to 2042. DOE will use the approach developed by EIA to forecast

fuel prices for the Federal Energy Management Program (FEMP). FEMP uses these prices to

estimate life­cycle costs of federal equipment procurements. For petroleum products, EIA uses

the average growth rate for the world oil price over the years 2010 to 2025, in combination with

the refinery and distribution markups from the year 2025, to determine the regional price

forecasts. Similarly, EIA derives natural gas prices from an average growth rate figure in

combination with regional price margins from the year 2025.

13.3 RESULTS

Results of the utility impact analysis will include changes in commercial electricity sales,

and installed capacity and generation by fuel type, for each trial standard level, in five­year

forecasted increments extrapolated to the year 2042.

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REFERENCES
 

1. EIA (Energy Information Administration). 2007. Annual Energy Outlook 2007, EIA,

Washington, D.C., Report No. DOE/EIA­0383(2007).

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