CHAPTER 1 5 . UTILITY IMPACT ANALYSIS

TABLE OF CONTENTS

15.1 INTRODUCTION

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- 1 15.2 METHODOLOGY

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- iCHAPTER 15. UTILITY IMPACT ANALY SIS

15.1 INTRODUCTION

In the utility impact analysis, DOE analyzes the changes in electric installed capacity and generation that result for each candidate standard s case for the notice of proposed rulemaking (NOPR)

. 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 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 Referen ce Case and for cases in which energy use is decremented to reflect the impact of standards. For the analysis of standards on refrigerated beverage vending machines

, DOE plans to use the version of NEMS based on AEO 201 3

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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.

• N EMS

- 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.

15.2 ME THODOLOGY

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 di fferences between

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 u se 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 a ssumptions, DOE refers to it by the name NEMS

BT (BT is DOE’s Building Technologies Program, under whose aegis this work has been performed).

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- 1marginal and average values may turn out to be smaller than the intrinsic uncertainties in the AEO.

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 s hapes 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 inter

related effects: the annua l 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
t otal 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 energ y 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 d efining 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 redu ction 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 C SL. The relationship between a reduction c in electricity generation (TWh) and t he 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). 2

NEMS

- BT provides output for the following capacity types: coa l, 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 int o a “peaking” category, and grouped pumped storage, fuel cells, and distributed generation (natural gas) into an “other” category.

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

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- 2REFERENCES

1. Energy Information Administration, Annual Energy Outlook 2013 with Projections to 2040 , 20 13. Washington, DC. < http://www.eia.doe.gov/oiaf/aeo/ >

2. Coughlin, K., H. Shen, P. Chan, B. McDevitt, and A. Sturges, Marginal Utility Sector Impacts of Reduced Electricity Demand , 2012.

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