### APPENDIX J. ESTIMATION OF UTILITY AND ENVIRONMENTAL RESULTS FROM NEMS-BT OUTPUT

TABLE OF CONTENTS
J.1 Allocation of Input Electricity Savings by Census Division and End Use ...................... J-2 J.2 Choice of Impact Multipliers ........................................................................................... J-2 J.3 Regression Smoothing of NEMS-BT Outputs ................................................................. J-5 J.4 Estimation of Interpolating Functions from Savings Multipliers .................................... J-7 J.5 Environmental Impacts .................................................................................................... J-9

LIST OF TABLES Table J.1.1 Shares of National Savings by Census Division Used in NEMS-BT ....................... J-2 Table J.1.2 Heating and Cooling Share for PTHP Equipment by Census Division .................... J-2 Table J.2.1 Comparison of Savings with Different Multipliers with Total Generation ............................................................................................................. J-3 Table J.2.2 Final Implied Multipliers by Equipment Class and Trial Standard Level ..................................................................................................................... J-4

LIST OF FIGURES Figure J.3.1 Example of Regression Smoothing Fits for Fossil-Fired and Total Installed Capacity (200X case for PTHP). ............................................................ J-7 Figure J.4.1 Response (Interpolating) Functions for Selected Generation Outputs, PTHP Case for 2025 ............................................................................... J-8 Figure J.5.1 Response (Interpolating) Functions for Carbon Dioxide, PTHP Case, for Years 2015, 2020, 2025 and 2030. ...................................................... J-10

J-i

### APPENDIX J. ESTIMATION OF UTILITY AND ENVIRONMENTAL RESULTS FROM NEMS-BT OUTPUT The effects of proposed energy conservation standards for packaged terminal air conditioners (PTACs) and packaged terminal heat pumps (PTHPs) was analyzed using a variant of National Energy Modeling System (NEMS) model, called NEMS-BT. 1 a 

### Because the size of national energy savings as a result of the proposed standards for PTACs and PTHPs are so small relative to the size of the entire electric utility sector, DOE used an estimation method involving regression smoothing and interpolation. This appendix describes the major elements of this method. To run a simulation in NEMS-BT model, the space-cooling load in the commercial building module is reduced annually according to the electricity savings estimated by the National Energy Savings (NES) spreadsheet model (see Chapter 11 of the TSD) for each trial standard level (TSL). The electricity savings increase over time as PTAC and PTHP equipment are replaced with more efficient equipment meeting the proposed conservation standards. The magnitude of the electricity decrement that would be required for NEMS-BT to produce stable results out of the range of numerical noise is greater than the highest TSL under consideration. Therefore, to estimate results fo r the TSLs evaluated here, a series of NEMS-BT simulations is performed using higher values for the input electricity savings. These simulations establish the relationship between the NEMS-BT output variables (electricity generation by fuel, installed electricity generation capacity, and emissions) and the electricity savings inputs. For each output variable, a regression model is estimated to represent an average response across the series of simulations. Impacts are obtained using predicted values from the regression models corresponding to the (smaller) levels of savings corresponding to TSLs. As discussed in Chapter 14, the utility and environmental impacts from an amended energy conservation standard on PTAC equipment can be expected to be different from a standard on PTHP equipment. Separate sets of runs with the NEMS-BT model were made for each type of equipment to distinguish these effects.

a DOE’s EIA approves of the name NEMS to describe onl y an official version of the model without any modification of the code or data. Because the analysis of PTAC and PTHP energy efficiency standard entails some minor code modifications and the model is run under po licy scenarios that are variations of DOE/EIA assumptions, the name NEMS-BT refers to the model as used here. (The Bu ilding Technologies [BT] program is one of the major program offices within DOE’s Office of Energy Efficiency and Renewable Energy. The Building Technologies program is responsible for promulga ting energy efficiency stan dards for the buildings sector mandated under the 2005 Energy Po licy Act and earlier federal legislation.

J-1

### J.1 Allocation of Input Electricity Savings by Census Division and End Use Although the utility and environmental impacts are national in scope, the NEMS-BT model operates at a census division level. Lacking sales information for PTAC/PTHP equipment by census division, an allocation of savings was made on the basis of population. The shares used to distribute the savings across census divisions are shown in Table J.1.1. The shares are held constant for the forecast period through 2030.
Table J.1.1 Shares of National Savings by Census Division Used in NEMS-BT
Census Division Share (%) New England 11.2% Middle Atlantic 14.1% East North Central 16.0% West North Central 6.8% South Atlantic 18.4% East South Central 6.0% West South Central 11.2% Mountain 6.5% Pacific 16.0% 

### For PTHP equipment, energy efficiency standards will yield electricity savings for both heating and cooling. Based on the building energy use simulations described in Chapter 7 of this TSD, an estimate of savings between heating and cooling was developed for each census division. The simulation results were weighted by state population estimates corresponding the locations employed in the analysis. The relative shares between heating and cooling vary slightly across trial standard levels for PTHP. As the shares for two of the trial standard levels were very close to each other (TSL 2 and TSL 6), the shares for TSL 6 were used develop heating and cooling savings inputs for NEMS-BT. The heating and cooling shares by census division are shown in Table J.1.2.
Table J.1.2 Heating and Cooling Share for PTHP Equipment by Census Division Census Division Cooling Heating New England 35% 65% Middle Atlantic 42% 58% East North Central 41% 59% West North Central 51% 49% South Atlantic 73% 27% East South Central 69% 31% West South Central 80% 20% Mountain 59% 41% Pacific 59% 41% 

### J.2 Choice of Impact Multipliers To gain some understanding of the how NEMS-BT would respond to various magnitudes of savings, a “reference” time series of savings was initially selected from the NES spreadsheet model. This reference series was selected as the savings that would result from highest level of TSLs for PTHP equipment with cooling capacity great than 10,000 Btu/h (i.e., representative cooling capacity of 12,000 Btu/h for standard sizes PTHPs as shown in Chapter 11). As described in Chapter 7, the energy savings for this equipment category are estimated

J-2

### approximately 25 percent higher than the equivalent-sized PTAC equipment. NEMS-BT was run for this stream of savings, as well as for higher multipliers (designated here with a suffix X), including 2X, 5X, 10X, 20X, 100X, 200X, and 300X. It was judged on the basis of graphical output and comparison of trends among the output variables, that the numerical noise from the model was overwhelming the impact of the savings decrement for the smaller multiplier factors up to 20X. b 

### Table J.2.1 compares the savings decrement applied to the model under various multipliers and how the magnitude of the savings compares with total electricity generation in EIA’s Annual Energy Outlook (AEO2008) reference case. 2 c


### Table J.2.1 Comparison of Savings with Different Multipliers with Total Generation

2015 2020 2025 2030

Multiplier Total Generation (TWh) 4,483 4,723 4,972 5,231
1X Savings (TWh) 0.039 0.076 0.103 0.125 % of total generation 0.001% 0.002% 0.002% 0.002% 100X Savings (TWh) 3.9 7.6 10.3 12.5 % of total generation 0.09% 0.16% 0.21% 0.24% 200X Savings (TWh) 7.8 15.2 20.6 25 % of total generation 0.17% 0.32% 0.41% 0.48% 300X Savings (TWh) 11.7 22.8 30.9 37.5 % of total generation 0.26% 0.48% 0.62% 0.72%

b The numerical noise stems, in part, from the fact that a precise balancing between the demand and supply sides of NEMS is not always achieved, given the iterativ e nature of the solution process.
c The reader should note that the values of the multipliers used here are solely dependen t on the initial (and arbitrary) choice of a particular PTAC/PTHP product and a specific trial standard level (TSL) for that product. The NEMSBT simulations were performed prior to the fi nal selection of TSL’s and so the 1X multiplier does not correspond to any specific TSL for a product category in previous sections of the re port. (The final estimate of energy savings for standard size (small + large capacity) PTHP equipment at TSL 6 is very close to the 1X value, having an actual multiplier of 1.032) However, it was judged that the sav ings decrements (in TWh) tested in NEMS-BT, shown in lower portion of , were in the relevant range of magn itudes to yield stable and robust predictions by the model and so additional runs using different multipliers were deemed unnecessary. For use in the predicting the impacts from the set of final TSLs, the sa vings decrement from any TSL was converted into an appropriate multiplier by scaling in proportion to the values shown in the first row of . Th is procedure is explained more fully below. This same scaling was used for both PTHP and PTAC equipment, with the savings for PTHP equipment allocated to cooling and heating. Table J.2.1

Table J.2.1

J-3

### Based on this testing, a decision was made to use the higher multipliers in the range of 100X through 300X. While these multipliers are large, they still do not yield large perturbations to the base case simulation. For example, as Table J.1.1 indicates, even at 100X in the year 2025 the total savings decrement applied to the model represents only about 0.5 percent of total electricity generation. Final Implied Multipliers by Equipment Class and Trial Standard Level Subsequent to the production of the NEMS simulations described in the previous section, some revisions were made to the final set of energy savings estimates for the NOPR. In addition, for purposes of estimating utility and environmental impacts for standard-size equipment, the two size equipment classes (equal or less than 10,000 Btu/h and greater than 10,000 Btu/h) were combined. To adjust for these changes, the difference between the final savings estimate (by equipment class and trial standard level) and the savings from a preliminary “reference” time series (PTHP, >10,000 Btu/h, at the largest TSL) was represented as a scale factor. The scale factor essentially adjusts the savings from particular equipment class and TSL to be consistent with the reference series and thus consistent with the interpolation procedure described above. The first column in Table K.2.2 displays the scale factors for each equipment class and TSL. d 

### The remaining columns display the implied multipliers from the three simulations performed with NEMS-BT for either PTACs or PTHPs (using their designations of 100X, 200X, and 300X). For example, after combining the size categories for PTHP equipment, the actual multipliers for TSL-7 were 52, 104, and 156. Because the savings for TSL 1 through 6 are smaller than those for TSL 7, the implied multipliers are larger than those for TSL 7. Table J.2.2 Final Implied Multipliers by Equipment Class and Trial Standard Level Implied Multipliers Scale Factor NEMSBT ("100X") NEMSBT ("200X") NEMSBT ("300X") Equipment Class PTAC - Std. Size TSL - 1,2,4 0.137 729 1,457 2,186 TSL - 3 0.307 326 652 977 TSL - A 0.728 137 275 412 TSL - 5 0.543 184 368 552 TSL - 6 0.834 120 240 360
PTAC - Non-Std. Size TSL - 1,2,4 0.042 2,359 4,718 7,077 TSL - 3 0.070 1,436 2,872 4,308 TSL - 5 0.107 936 1,872 2,809

d The scale factors can also be viewed as interpolating values relative to the set of NEMS-BT impact runs. Thus, for example, if an impact upon a particular variable from the “1X” case in the original set of simulations was interpolated to be a value of, say, 0.10, then the impact for TSL-3 for standard size PTAC equipment would be 0.224 x 0.10 = 0.022.

J-4PTHP - Std. Size TSL - 1 0.267 375 750 1,125 TSL - 2,3 0.558 179 359 538 TSL - A 0.666 150 300 450 TSL - 4,5 0.898 111 223 334 TSL - 6 1.032 97 194 291
PTHP - Non-Std. Size TSL - 1 0.055 1,804 3,609 5,413 TSL - 2,3 0.076 1,317 2,634 3,951 TSL - 4,5 0.128 781 1,562 2,343 Implied Multipliers Scale Factor NEMSBT ("100X") NEMSBT ("200X") NEMSBT ("300X") Equipment Class PTAC - Std. Size TSL - 1,2,4 0.137 729 1,457 2,186 TSL - 3 0.307 326 652 977 TSL - A 0.728 137 275 412 TSL - 5 0.543 184 368 552 TSL - 6 0.834 120 240 360
PTAC - Non-Std. Size TSL - 1,2,4 0.042 2,359 4,718 7,077 TSL - 3 0.070 1,436 2,872 4,308 TSL - 5 0.107 936 1,872 2,809
PTHP - Std. Size TSL - 1 0.267 375 750 1,125 TSL - 2,3 0.558 179 359 538 TSL - A 0.666 150 300 450 TSL - 4,5 0.898 111 223 334 TSL - 6 1.032 97 194 291
PTHP - Non-Std. Size TSL - 1 0.055 1,804 3,609 5,413 TSL - 2,3 0.076 1,317 2,634 3,951 TSL - 4,5 0.128 781 1,562 2,343 

### J.3 Regression Smoothing of NEMS-BT Outputs Even at the selected multiplier levels shown in Table J.1.1, the simulations with NEMS-BT produces considerable year-to-year variation that appears to be caused by numerical noise from the model solution. This variation appears to affect the outputs related to specific generation fuel and technologies more so than total generation or total installed capacity. For the utility impact assessment, it is more important to identify distinct trends in the utility sector adjustment process rather than year-to-year variation that may or may not be spurious results from the model solution process.

J-5

### To reduce the potential effect of numerical noise from NEMS-BT simulation, a smoothing regression was estimated for each of the model output variables. The output variables are measured as the differences between the (AEO) reference case and the energy efficiency standards case. The formulation of the smoothing regression was a simple quadratic function of time (in years) with the following form: Y(T) = a1 x T + a2 x T 2 

### + u Eq. K.1 where Y = Output variable for time period T (difference from reference case) T

= Time in years, T = 0 in 2011, T = 1 in 2012, etc. a1,a2 = estimated regression coefficients
u = random disturbance term. The regression specification is such that the fitted (predicted) value of the variable is forced through the origin in the year the prior to the implementation of the standard (2011). By forcing the impact to be zero in 2011, this procedure generates estimated impacts that typically could be expected to change in a systematic fashion beginning in 2012. Figure J.3.1 illustrates this procedure for the differences in total installed capacity and the three types of fossil fuel capacity. The particular case shown is for the PTHP equipment at the 200X level of savings. Clearly, NEMS-BT indicates a very smooth path of differences in total generation capacity as shown in the top left panel of the figure. (In this case, the regression smoothing would not be necessary.) For fossil steam plants,the simulation reveals a u-shaped curve that shows a reduction in capacity until around 2025 and then rising sharply after that. The deviations from the fitted trend line are more pronounced for combined cycle plants. Nevertheless, over the entire forecast period, the downward trend in the capacity of these plantsis very apparent from the graph. The approach in this analysis is to abstract these very shortterm deviations from what appears to be a long-term trend. Finally, for combustion turbines, the deviations from a smooth downward trend are relatively small. The use of the quadratic specification is most apparent here as the decline in capacity accelerates during the latter portion of the forecast period.

J-6Total Generation

-14 -12 -10

-8 -6 -4 -2 0 2 2010 2015 2020 2025 2030Difference (GW)

NEMS-BT Fitted Fossil Steam

-5 -4 -3 -2 -1 0 1 2 3 2010 2015 2020 2025 2030Difference (GW) NEMS-BT Fitted

Combined Cycle

-2 -1.5

-1 -0.5

0 0.5

2010 2015 2020 2025 2030Difference (GW)

NEMS-BT Fitted Combustion Turbine

-7 -6 -5 -4 -3 -2 -1 0 1 2010 2015 2020 2025 2030Difference (GW)

NEMS-BT Fitted



### Figure J.3.1 Example of Regression Smoothing Fits for Fossil-Fired and Total Installed Capacity (200X case for PTHP). J.4 Estimation of Interpolating Functions from Savings Multipliers The development of utility and environmental im pacts focused on specific years from the NEMS-BT simulations: 2015, 2020, 2025 and 2030. For each output variable (e.g., coal-fired electricity generation), the predicted values from the trend regression were extracted for each savings multiplier level (100X, 200X, and 300X). A subsequent linear regression was performed using these values for the dependent variable and the values of the saving multiplier as the independent or explanatory variable. The y-intercept of this regression is forced through the origin. This restriction ensures that the predicted value of a NEMS-BT output variable is zero when the savings multiplier is zero. Predicted values for non-zero multipliers are calculated by taking the estimated regression coefficient (slope) times the value of the savings multiplier. Figure J.4.1 shows several examples of this estimation approach. The magnitude of the energy savings multiplier is plotted on the x-axis against the total reduction in generation capacity for the year 2025. The results shown are based on three simulations for PTHP equipment. The fitted 2025 values from the smoothing regression of the NEMS-BT output are shown in the large solid (black) diamonds. In the case of total generation capacity, the linear regression line is closely aligned to the three points corresponding to the 100X, 200X, 300X

J-7J-8 Total Generation

-35 -30 -25 -20 -15 -10

-5 0 0 50 100 150 200 250 300 350

Savings MultiplierDifference (TWh) Coal

-25 -20 -15 -10

-5 0 0 50 100 150 200 250 300 350

Saving MultiplierDifference(TWh)

Natural Gas

-2 0 2 4 6 8 10 0 50 100 150 200 250 300 350

Savings MultiplierDifference (TWh) Nuclear

-20 -15 -10 -5 0 5

0 100 200 300 400

Savings MultiplierDifference (TWh)



### Figure J.4.1 Response (Interpolating) Functions for Selected Generation Outputs, PTHP Case for 2025 savings multipliers. Within this range of savings, the plot demonstrates the impact on total capacity predicted by the model is basically proportional to the magnitude of the savings. For the other generation types shown Figure J.4.1, the responses deviate from strict proportionality. For example, for natural gas, the response at the 300X is greater than either the 100X or 300X levels. The approach taken here essentially produces a weighted average of the responses across these various savings multipliers. The predicted value of a NEMS-BT output variable for a given standards level is interpolated along the regression line estimated for that variable. The savings from a particular standards case is first converted into a savings multiplier using the relationships shown in Table J.2.1. Thus, for example, if the trial standard level for a particular product were to yield a decrement of 0.052 TWh in 2025, the savings multiplier would be calculated as 0.5 (= 0.052/0.103, where 0.103 is 1X in 2025 from Table J.2.1). For total generation, the estimated response coefficient is -0.10 (e.g., the slope of regression line in the top left panel Figure J.4.1). Thus, the estimated impact on total generation in 2020 from this specific trial standard level would be 0.5 x -0.10 = -0.05 TWh.

### The entire estimation process was performed separately for PTAC and PTHP equipment. As described in Chapter 14, the response coefficients for total generation, for the same total savings decrement, was somewhat different for PTAC versus PTHP equipment. The impact on installed generation capacity is significantly higher for PTAC equipment as compared to PTHP equipment. J.5 Environmental Impacts The general approach for estimating the impacts on the utility sector was also used to develop an environmental assessment in terms of changes in emissions. Annual values of the emissions for NO x 

### , mercury, and carbon dioxide were extracted from the relevant tables produced by NEMS. Similar to examples shown in Figure J.3.1, the projections of emissions from 2012 through 2030 were smoothed using the quadratic function in time discussed above. Response functions were then estimated at five-year intervals between 2015 and 2030. Figure J.5.1 shows the estimated response (or interpolating) functions for carbon dioxide emissions for PTHP equipment. In general, total carbon emissions are approximately proportional to the level of the saving decrement (for the savings decrements shown in Table J.2.1 corresponding to 100X, 200X, and 300X). The scale of the y-axis is held constant for each of the plots and so the clockwise rotation of the slopes across the years 2015 through 2020 reflects the increasing reduction in emissions over these years. The slope is somewhat smaller in the latter years for this particula r series of simulations. This behavior likely reflects a sharp reduction in nuclear capacity by 2030, particularly in the 200X and 300X cases, which tends to offset some of the reductions in carbon emissions from fossil fuel generation (see Chapter 14 for impacts on particular generation technologies).

J-9Carbon Dioxide Emissions (2015)

-50 -40 -30 -20 -10

0 0 50 100 150 200 250 300 350

Savings MultiplierDifference (MMT-CE) Carbon Dioxide Emissions (2020)

-50 -40 -30 -20 -10

0 0 50 100 150 200 250 300 350

Savings MultiplierDifference (MMT-CE)

Carbon Dioxide Emissions (2025)

-50 -40 -30 -20 -10

0 0 50 100 150 200 250 300 350

Savings MultiplierDifference (MMT-CE) Carbon Dioxide Emissions (2030)

-50 -40 -30 -20 -10

0 0 50 100 150 200 250 300 350

Savings MultiplierDifference (MMT-CE)



### Figure J.5.1 Response (Interpolating) Functions for Carbon Dioxide, PTHP Case, for Years 2015, 2020, 2025 and 2030.

J-10J-11 

### REFERENCES 1. U.S. Department of Energy. Energy Information Administration. National Energy Modeling System: An Overview 2003. (DOE/EIA-0581(2003), March 2003. http://tonto.eia.doe.gov/reports/reports_kindD.asp?type=model%20documentation. 2. U.S. Department of Energy/Energy Information Administration (DOE/EIA), Annual Energy Outlook 2008 , April 2008. Washington, D.C. DOE/EIA-0383(2007).