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CHAPTER 14. UTILITY IMPACT ANALYSIS

TABLE OF CONTENTS

14.1 INTRODUCTION ......................................................................................................... 14-1

14.2 METHODOLOGY ........................................................................................................ 14-1
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CHAPTER 14. UTILITY IMPACT ANALYSIS

14.1 INTRODUCTION

In the utility impact analysis, DOE analyzes the changes in electric installed capacity and 

generation that result for each candidate standards case.

The utility impact analysis uses a variant of the DOE/Energy Information Administration 

(EIA)’s National Energy Modeling System (NEMS).a

 NEMS is a public domain, multi-sectored, 

partial equilibrium model of the U.S. energy sector. Each year, DOE/EIA uses NEMS to produce an 

energy forecast for the United States, the Annual Energy Outlook (AEO). DOE uses a variant of this 

model, referred to as NEMS-BT,b

1

to account for selected utility impacts of energy conservation 

standards. DOE’s analysis consists of a comparison between model results for the most recent AEO

Reference Case and for cases in which energy use is decremented to reflect the impact of standards. 

For the analysis of standards on furnace fans, DOE used the version of NEMS based on AEO 

2012. 

NEMS-BT has a number of advantages that have led to its use in the analysis of energy 

conservation standards: 

• NEMS-BT uses a set of assumptions that are well known and fairly transparent, due 

to the exposure and scrutiny each AEO receives. 

• NEMS-BT is updated each year, with each edition of the AEO, to reflect changes in 

energy prices, supply trends, regulations, etc.

• The comprehensiveness of NEMS-BT permits the modeling of interactions among 

the various energy supply and demand sectors. 

14.2 METHODOLOGY

DOE uses NEMS-BT to estimate the marginal impacts of reduction in energy demand on 

the energy supply sector. In principle, marginal values should provide a better estimate of the 

actual impact of energy conservation standards. In practice, the numerical differences between 

marginal and average values may turn out to be smaller than the intrinsic uncertainties in the 

AEO. 

 

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

documentation. A useful summary is National Energy Modeling System: An Overview 2003, DOE/EIA-0581(2003), 

March, 2003. 

b DOE/EIA approves use of the name NEMS to describe only an official version of the model without any 

modification to code or data. Because this analysis entails some minor code modifications and the model is run 

under various policy scenarios that are variations on DOE/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). 
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NEMS uses predicted growth in demand for each end use to build up a projection of the 

total electric system load growth. The system load shapes are converted internally to load 

duration curves, which are then used to estimate the most cost-effective additions to capacity. 

When electricity demand deviates from the AEO reference case, in general there are three interrelated effects: the annual generation (TWh) from the stock of electric generating capacity 

changes, the total generation capacity itself (GW) may change, and the mix of capacity by fuel 

type may change. Each of these effects can vary for different types of end use. The change in 

total generating capacity is sensitive to the degree to which the end-use is peak coincident, while 

the capacity mix is sensitive to the hourly load shape associated with the end use. 

To model the impact of a standard, DOE inputs a reduction to annual energy demand for 

the corresponding end use in the appropriate start year. The NEMS-BT model is run with the 

decremented energy demand to determine the modified build-out of capacity and total 

generation. Regional effects of a standard can be accounted for by defining the energy demand 

decrement as a function of census division. 

The output of the NEMS-BT analysis includes the effective marginal heat rate (ratio of 

the change in fuel consumption in quads to the change in generation in TWh), and the capacity 

reduction by fuel type for a given reduction in total generation. DOE uses the site energy savings 

multiplied by a T&D loss factor to estimate the reduction in generation for each TSL. The 

relationship between a reductionc

2

in electricity generation (TWh) and the reduction in capacity 

(GW) is estimated based on the output of NEMS-BT model runs using the end-use specific 

energy demand decrement. Details on the approach used may be found in Coughlin (2012).

NEMS-BT provides output for the following capacity types: coal, nuclear, 

combined cycle (natural gas), renewable sources, oil and natural gas steam, 

combustion turbine/diesel, pumped storage, fuel cells, and distributed generation (natural gas). 

DOE grouped oil and natural gas steam and combustion turbine/diesel into a “peaking” category, 

and grouped pumped storage, fuel cells, and distributed generation (natural gas) into an “other” 

category.

In general, energy conservation standards impact primarily fossil combustion (coal, 

natural gas and diesel) and renewables. Pumped storage and nuclear power are very insensitive 

to small changes in demand, while fuel cells and distributed generation make up a very small 

fraction (less than 1%) of the generation capacity base.

 

c These reductions are defined relative to the AEO Reference case.
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REFERENCES

1. Energy Information Administration, Updated Annual Energy Outlook 2009 Reference 

Case Service Report, 2009. Washington, DC. Report No. DOE/EIA-0383(2009). 

<http://www.eia.doe.gov/oiaf/aeo/>