CHAPTER 13. UTILITY IMPACT ANALYSIS TABLE OF CONTENTS 13.1 INTRODUCTION
.................................................. 13-1 13.2 ASSUMPTIONS
................................................... 13-2 13.3 METHOD
........................................................ 13-3 13.4 RESULTS
........................................................ 13-5 LIST OF TABLES Table 13.4.1 Liqui d-Immersed Transformers: Trial Standard Level 1 Forecast
......... 13-6

Table 13.4.11 Dry-Type, Medium -Voltage Transformers: Trial Standard Level 1 Forecast Table 13.4.12 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 Forecast Table 13.4.13 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 3 Forecast Table 13.4.14 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 4 Forecast Table 13.4.15 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 5 Forecast Table 13.4.16 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 6 Forecast Table 13.4.17 Liquid-Immersed Trial Standard Level C High Economic Growth Forecast Table 13.4.18 Liquid-Immersed Trial Standard Level C Low Economic Growth Forecast Table 13.4.2 Liqui d-Immersed Transformers: Trial Standard Level 2 Forecast
......... 13-7 Table 13.4.3 Liqui d-Immersed Transformers: Trial Standard Level 3 Forecast
......... 13-8 Table 13.4.4 Liqui d-Immersed Transformers: Trial Standard Level 4 Forecast
......... 13-9 Table 13.4.5 Liqui d-Immersed Transformers: Trial Standard Level 5 Forecast
........ 13-10 Table 13.4.6 Liqui d-Immersed Transformers: Trial Standard Level 6 Forecast
........ 13-11 Table 13.4.7 Liqui d-Immersed Transformers: Trial Standard Level A Forecast
....... 13-12 Table 13.4.8 Liqui d-Immersed Transformers: Trial Standard Level B Forecast
........ 13-13 Table 13.4.9 Liqui d-Immersed Transformers: Trial Standard Level C Forecast
........ 13-14 Table 13.4.10 Liqui d-Immersed Transformers: Trial Standard Level D Forecast
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......................................................... 13-17

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......................................................... 13-19

......................................................... 13-20

......................................................... 13-21

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......................................................... 13-23 Table 13.4.19 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 High Economic Growth Forecast
............................................. 13-24 Table 13.4.20 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 Low Economic Growth Forecast
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13-iCHAPTER 13. UTILITY IMPACT ANALYSIS 13.1 INTRODUCTIONThe Department of Energy (DOE) analyzed the effects of distribution transformer energyeff iciency standard levels on the electric utility industry as part of the notice of proposed rulemaking (NOPR) analysis and in preparation for a final rule that adopted an energy conservation standard, DOE used a variant of the U.S. DOE/Energy Information Administration (EIA)’s National Energy Modeling System (NEMS). aNEMS, which is available in the public domain, is a large, multi-sectoral, partial equilibrium model of the U.S. energy sector. DOE/EIA uses NEMS to produce a widely recognized baseline energy forecast for the U.S. through 2030, the Annual Energy Outlook 2006 ( AEO2006). 1 DOE used a variant known as NEMS-BT to provide key inputs to the analysis. bThe utility impact analysis consisted of a comparison between model results for the AEO2006 Reference Case and for policy cases in which alternative standards are in place. DOE conducted the utility impact analysis as policy deviations from the AEO2006, appl ying 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 AEO2006 Reference Case, as are the prospects for natural gas supply. The utility impact analysis reports the changes in installed capacity and generation, by fuel type, that result for each trial standard level, as well as changes in end-use electricity sales. While the AEO2007 el ectricity price forecast data was available in time for preparation of the final rule, the full AEO2007 forecast was not available at the time DOE performed the utility and environmental impact analysis. DOE therefore used AEO2006 for the utility and environmental analysis. Following completion of the utility and environmental analysis and after the full AEO2007 became available, DOE compared the AEO2006 and AEO2007 and found the forecasts of electricity prices, the marginal generation mix and emissions factors in the AEO2007 and AEO2006 forecasts were very similar. The two forecasts provide the same marginal fractions of coal and natural gas generation (within 3.5%), and have marginal CO 2emission factors that differ by less than 2%.

a For more information on NEMS, r efer to the U.S. Departmen t of Energy, Energy Information Administration documentation. A useful summary is National Energy Modeling System: An Overview 2003 , DOE/EIA0581(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 DOE runs the model under various policy scenarios that are variations on DOE/EIA assumptions, DOE refers to it by the name NEMS-BT (BT is DOE = s Building Technologies Program, under whose aegis this work has been performed). NEMS-BT was previously called NEMS-BRS. 13-1DOE calculated the comparison marginal generation mix and CO2emissions factors for AEO2006 and AEO2007 by examining the difference in generation and emissions for the High Economic Growth Case with the Low Economic Growth Case output for the two forecasts. For the difference between the two cases, DOE estimated the relative amount of electricity supply that was provided by coal and natural gas generation and weighted the forecast of the relative capacity by the forecast annual electricity savings from the adopted standard. DOE found that AEO2006 forecasted that 74.4% of the weighted average marginal generation would be provided by coal while 12.9% would be provided by natural gas. Meanwhile AEO2007 forecasted that 71.2% of weighted average marginal generation capacity would be provided by coal while 11.5% would be provided by natural gas. The similar generation mix results in forecasted weighted average CO 2 emissions factors that are within 2% of each other for the two forecasts. As a result of these verified similarities between AEO2006 and AEO2007 forecasts, DOE assumed that the utility and environmental results derived from the AEO2006 forecast is a good approximation of the results that would have been calculated from AEO2007
. 13.2 ASSUMPTIONS NEMS-BT has several advantages that have led to its adoption as the source for basic forecasting in DOE’s energy-efficiency analyses for appliance standards. NEMS-BT relies on a set of assumptions that are well-known and fairly transparent, due to the exposure and scrutiny each AEO receives. In addition, the comprehensiveness of NEMS-BT permits the modeling of interactions among the various energy supply and demand sectors and the economy as a whole, so it produces a complete picture of the effects of energy-efficiency standards. Because it explicitly simulates the impact on the entire energy sector, NEMS-BT provides an accurate estimation of marginal effects. This approach yields better indicators of actual effects than estimates based on industry-wide average values. To be consistent with the system load data it used to develop the input load decrement for eac h alternative trial standard level, DOE replaced the default NEMS system load shape in the AEO2006 Reference Case with one that represents normalized weather conditions for a typical meteorological year (TMY), which is referred to as the TMY system load. 2 DOE’s reference case is thus called the TMY System Load Reference Case. The differences between the AEO2006 Reference Case and the TMY System Load Reference Case are minor. The total installed electric generation capacity for the TMY System Load Reference Case is only 0.1 percent higher, and total electricity generation 0.1 percent higher, than the AEO2006 Reference Case in year 2030. The utility impact analysis used the assumptions of the AEO2006 and treated tr ansformer efficiency standards as variations in policy. The input load decrement represents an hourly reduction to the substituted system load that corresponds to the energy savings resulting from a distribution transformer standard. Because the implementation of distribution transformer standards reduces electricity demand by less than two percent (between 0.01 and 1.1 percent in 2030) of total U.S. generation in any given year, its effect cannot be detected directly by simulations. Therefore, DOE simulated larger reductions in demand, and interpolated results as

13-2the difference between the TMY System Load Reference Case and the standards result. DOE assumed the effects to be linear within the range of interpolation. DOE also explored deviations from some of the AEO2006 Reference Case assum ptions, by representing two alternative futures: the High and Low Economic Growth Cases of AEO2006. The TMY System Load Reference Case corresponds to medium growth. The High Economic Growth Case assumes higher projected growth rates for population, labor force, and labor productivity, resulting 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 Economic Growth Case. The High Growth Case reflects an average annual growth in gross domestic product of 3.3 percent per year compared with 3.0 percent per year in the Reference Case, and 2.8percent per year in the Low Growth Case. Different economic growth scenarios affect the rate of growth of electricity demand. DOE ran the High and Low Economic Growth Cases for the final rule standard level of each of two product classes: specifically, liquid-immersed transformers Trial Standard Level C; and dry-type, medium-voltage transformers Trial Standard Level 2. Tables 13.4.17 and 13.4.20 present the results for these standard levels, for these High and Low Economic Growth scenarios.

13.3 METHOD The utility impact analysis consisted of NEMS-BT forecasts for generation, installed ca pacity, and end-use energy consumption. DOE presents the results in five-year increments to year 2030, including High and Low Economic Growth Cases for the adopted standard levels. Beyond year 2030, an extrapolation to 2038 for each trial standard level represents a simple replication of the year 2030 results. DOE determined the size of the load decrement using data for the per-unit energy savings developed in the life-cycle cost (LCC) and payback period (PBP) analysis (Chapter 8 of this technical support document (TSD)) and the shipments forecast developed for the national impact analysis (Chapter 9). Because the predicted reduction in capacity additions is sensitive to the peak load impact of

the alternative standard, DOE developed a mathematical model of the hourly distribution transformer savings as a function of the hourly system load for each trial standard level. It applied energy decrements to each month of each specified forecast year, for three day types (week day, weekend, and peak day), for each hour of the day. DOE used a double-decrement approach to model the utility sector effect; it made two energy decrements, one to the NEMS-BT system load and the other to end-use consumption. 3 Making a decrement to the hourly system load ensured that the utility impacts from the standard alternative were accurately represented and properly reflected the hourly decrements calculated using the TMY System Load. 4

13-3In addition, because NEMS-BT is essentially an energy model in which changes made to load shapes do not propagate to the demand modules, DOE decreased the energy from refrigeration end use in the commercial energy demand sector by an equivalent amount. Because no specific end use for distribution transformers is represented in NEMS-BT, DOE needed to decrease demand-side consumption to maintain an energy balance on the supply and demand sides of the model. DOE chose the refrigeration end use because it most closely represents the peak load behavior of distribution transformers. In the commercial demand module, energy is forecasted on an annual basis, so DOE took an annual decrement by region from refrigeration end-use consumption. To avoid double-counting—because energy is being taken out of both the electricity load shapes and the end-use energy accounting—DOE added back a compensating restoration factor in the electric utility module. Therefore, following this approach, DOE applied the energy decrement twice, but restored one of them. This approach guaranteed that both the energy and load sides of NEMS-BT would be consistent with the estimated energy savings. Because the energy savings from distribution transformer standards are too small to produce stable power sector results in NEMS-BT, DOE estimated results for the trial standard levels using interpolation. To run a simulation in NEMS-BT, DOE reduced the system electricity load and commercial demand use annually, according to the energy savings estimated by the national energy savings (NES) Spreadsheet Model (see Chapter 10 in this TSD) for each trial standard level. These energy savings increase over time. The magnitude of the energy decrement that would be required for NEMS-BT to produce stable results out of the range of numerical noise is greater than the highest standard level. Therefore, to estimate results for the trial standard levels that DOE considered, DOE carried out a series of NEMS-BT runs, using highervalues for the input energy savings. These runs established the relationship between the NEMSBT outputs (e.g., installed capacity reductions, emissions reductions) and the energy savings inputs. DOE obtained results for energy savings corresponding to the trial standard levels using linear interpolation. DOE then used the estimated reduction in total fuel generation at each trial standard level, as determi ned by interpolation, to determine emissions savings. First, it calculated annual marginal emissions rates for each of the simulations in each standard level, based on the actual output from NEMS-BT. Marginal emissions rates incorporate both effects of the standards—the emissions saved by the reduction in total generation, and the slight change in the emissions characteristics of the whole power sector that result from the slight change in plants used to generate electricity (dispatch) and capacity expansion. The net effect on the entire system is very small and, typically, the overall effect on emissions can be fully attributed to the reduced generation capacity. DOE then used the marginal emissions rates to determine the annual marginal emissions rates for each trial standard level (at multipliers of the trial standard level savings) by taking a simple average. The current time horizon of NEMS-BT is 2030, yet other parts of the distribution tra nsformer energy-efficiency standards analysis extend to the year 2038. It is not feasible to extend the forecast period of NEMS-BT for the purposes of this analysis, nor does DOE/EIA have an approved method for extrapolation of many outputs beyond 2030. While it might seem 13-4reasonable in general to make simple linear extrapolations of results, in practice this is not advisable because outputs could be contradictory. For example, changes in the fuel mix implied by extrapolations of those outputs could be inconsistent with the extrapolation of marginal emissions factors. An analysis of various trends sufficiently detailed to guarantee consistency is beyond the scope of this work, and, in any case, would involve a great deal of uncertainty. Therefore, all extrapolations beyond 2030 are simple replications of year 2030 results. In this way, DOE guaranteed that the results would be consistent. As with the AEOReference Case in general, the implicit assumption is that the regulatory environment does not deviate from the current known situation during the extrapolation period. Only changes that have been announced with date-certain introduction are included in NEMS-BT. To emphasize the extrapolated results in the results tables, DOE shaded them in grey to distinguish them from actual NEMS-BT results.
13.4 RESULTS Tables 13.4.1 through 13.4.16 present the results for the various trial standard level cases f or each of the two product classes: liquid-immersed and dry-type, medium-voltage transformers. Each table shows forecasts using interpolated results as described in section 13.3 above for commercial energy sales, total U.S. electricity generation, and installed capacity. Commercial energy sales fall for each standard level compared to the TMY System Load Re ference Case, due to the decrement made to commercial refrigeration. The decrease in sales is comparable to the amount of energy that the NES Model predicts will be saved by each standard, ranging from less than 0.01 percent to over 2.2 percent of total commercial electricity sales in the year 2030. For each standard level, total U.S. electricity generation decreases relative to the TMY System Load Reference Case, by nearly 0.6 percent in year 2030 of the maximum savings case (liquid-immersed transformer Trial Standard Level 6), but only by less than 0.01 percent in dry-type, medium-voltage transformer Trial Standard Level 1. Total installed capacity is also slightly reduced by each standard level, up to just over 0.6 percent in the final year of the maximum savings case. The results under the High and Low Economic Growth cases are presented for the adopted standard level in Tables 13.4.17 through 13.4.20. Under the High Economic Growth scenario, the savings have a higher impact, while the Low Economic Growth scenario results in a lower impact.

13-5Table 13.4.1 Liquid-Immersed Transformers: Trial Standard Level 1 Forecast

13-6Table 13.4.2 Liquid-Immersed Transformers: Trial Standard Level 2 Forecast

13-7Table 13.4.3 Liquid-Immersed Transformers: Trial Standard Level 3 Forecast

13-8Table 13.4.4 Liquid-Immersed Transformers: Trial Standard Level 4 Forecast

13-9Table 13.4.5 Liquid-Immersed Transformers: Trial Standard Level 5 Forecast

13-10Table 13.4.6 Liquid-Immersed Transformers: Trial Standard Level 6 Forecast

13-11Table 13.4.7 Liquid-Immersed Transformers: Trial Standard Level A Forecast

13-12Table 13.4.8 Liquid-Immersed Transformers: Trial Standard Level B Forecast

13-13Table 13.4.9 Liquid-Immersed Transformers: Trial Standard Level C Forecast

13-14Table 13.4.10 Liquid-Immersed Transformers: Trial Standard Level D Forecast

13-15Table 13.4.11 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 1 Forecast

13-16Table 13.4.12 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 Forecast

13-17Table 13.4.13 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 3 Forecast

13-18Table 13.4.14 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 4 Forecast

13-19Table 13.4.15 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 5 Forecast

13-20Table 13.4.16 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 6 Forecast

13-21Table 13.4.17 Liquid-Immersed Trial Standard Level C High Economic Growth Forecast

13-22Table 13.4.18 Liquid-Immersed Trial Standard Level C Low Economic Growth Forecast

13-23Table 13.4.19 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 High Economic Growth Forecast

13-24Table 13.4.20 Dry-Type, Medium-Voltage Transformers: Trial Standard Level 2 Low Economic Growth Forecast

13-25REFERENCES 1. U.S. Department of Energy - Energy Information Administration. Annual Energy Outlook 2005: With Projections Through 2025. Ja nuary, 2005. Washington, DC. Report No. DOE/EIA-0383(2005). <http://www.eia.doe.gov/oiaf/aeo/index.html> 2. U.S. Department of Energy-Office of Building Technologies. Technical Support Document: Energy Conservation Program for Commercial and Industrial Equipment: Energy Conservation Standards for Commercial Unitary Air Conditioners and Heat Pumps - ANOPR Version. Appendix 0. 200 4. U.S. Department of Energy. Washington, DC. Report No. LBNL-53983. 3. LaCommare, K. H., E. Gumerman, C. Marnay, P. Chan, and K. Coughlin. A New Approach for Modeling the Peak Utility Impacts from a Proposed CUAC Standard. 2004. Lawrence Berkeley National Laboratory. Berkeley, CA. Report No. LBNL-55269. 4. U.S. Department of Energy-Office of Building Technologies. Technical Support Document: Energy Conservation Program for Commercial and Industrial Equipment: Energy Conservation Standards for Commercial Unitary Air Conditioners and Heat Pumps - ANOPR Version. Chapter 6. 200 4. U.S. Department of Energy. Washington, DC. Report No. LBNL-53983.

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