APPENDIX J. ESTIMATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS­BT OUTPUT

TABLE OF CONTENTS

J.1 Allocation of Input Electricity Savings by Census Division and End Use...................... J­2

J.2 Choice of Impact Multipliers........................................................................................... J­2

J.3 Regression Smoothing of NEMS­BT Outputs................................................................. J­5

J.4 Estimation of Interpolating Functions from Savings Multipliers.................................... J­6

J.5 Environmental Impacts.................................................................................................... J­8

LIST OF TABLES

Table J.1.1 Shares of National Savings by Census Division Used in NEMS­BT .......................J­2

Table J.1.2 Heating and Cooling Share for PTHP Equipment by Census Division ....................J­2

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

Generation.............................................................................................................J­3

Table J.2.2 Final Implied Multipliers by Equipment Class and Trial Standard

Level .....................................................................................................................J­4

LIST OF FIGURES

Figure J.3.1 Example of Regression Smoothing Fits for Fossil­Fired and Total

Installed Capacity (200X case for PTHP).............................................................J­6

Figure J.4.1 Response (Interpolating) Functions for Selected Generation

Outputs, PTHP Case for 2025...............................................................................J­7

Figure J.5.1 Response (Interpolating) Functions for Carbon Dioxide, PTHP

Case, for Years 2015, 2020, 2025 and 2030.........................................................J­8

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APPENDIX J. ESTIMATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS­BT 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

1a of National Energy Modeling System (NEMS) model, called NEMS­BT. 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 NEMS­BT model, the space­cooling 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 NEMS­BT to

produce stable results out of the range of numerical noise is greater than the highest TSL under

consideration. Therefore, to estimate results for the TSLs evaluated here, a series of NEMS­BT

simulations is performed using higher values for the input electricity savings. These simulations

establish the relationship between the NEMS­BT 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 NEMS­BT model were made for

each type of equipment to distinguish these effects.

a DOE’s EIA approves of the name NEMS to describe only 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 policy scenarios that are variations of DOE/EIA assumptions,

the name NEMS­BT refers to the model as used here. (The Building 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 promulgating energy efficiency standards for the buildings sector mandated under the

2005 Energy Policy Act and earlier federal legislation.

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EERE-2007-BT-STD-0012 COMMENT 02
J.1 Allocation of Input Electricity Savings by Census Division and End Use

Although the utility and environmental impacts are national in scope, the NEMS­BT

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 NEMS­BT

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 NEMS­BT. 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 NEMS­BT 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

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EERE-2007-BT-STD-0012 COMMENT 02
approximately 40 percent higher than the equivalent­sized PTAC equipment. NEMS­BT 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

b up to 20X. 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

2c EIA’s Annual Energy Outlook (AEO2007) reference case.

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

2015 2020 2025 2030

Multiplier Total Generation (TWh) 4,392 4,722 5,038 5,397

1X Savings (TWh) 0.039 0.076 0.103 0.125

% of total generation 0.002% 0.004% 0.005% 0.006%

100X Savings (TWh) 3.9 7.6 10.3 12.5

% of total generation 0.19% 0.38% 0.51% 0.62%

200X Savings (TWh) 7.8 15.2 20.6 25

% of total generation 0.39% 0.75% 1.02% 1.23%

300X Savings (TWh) 11.7 22.8 30.9 37.5

% of total generation 0.58% 1.13% 1.53% 1.85%

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 standard­size 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

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 iterative nature of the solution process.

The reader should note that the values of the multipliers used here are solely dependent 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 final 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 report. However, it was judged that the savings

decrements (in TWh) tested in NEMS­BT, shown in lower portion of Table J.2.1, were in the relevant range of

magnitudes 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 savings decrement

from any TSL was converted into an appropriate multiplier by scaling in proportion to the values shown in the first

row of Table J.2.1. This 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.

J­3

c

EERE-2007-BT-STD-0012 COMMENT 02
equipment class and trial standard level) and the savings from the initial “reference” time series

(PTHP, >10,000 Btu/h, at TSL 7) 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

d TSL. The remaining columns display the implied multipliers from the three simulations

performed with NEMS­BT 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 TSL­7 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

Standard Size PTACs

TSL – 1,2,4 0.100 1,000 2,000 3,000

TSL – 3 0.224 446 893 1,339

TSL – 5 0.397 252 504 755

TSL – 6 0.611 164 327 491

TSL – 7 1.379 73 145 218

Non­Standard Size PTACs

TSL – 1,2,4 0.031 3,266 6,533 9,799

TSL – 3 0.050 1,984 3,968 5,951

TSL – 5 0.078 1,290 2,581 3,871

TSL – 6 0.152 657 1,315 1,972

TSL – 7 0.209 478 957 1,435

Standard Size PTHPs

TSL – 1 0.192 520 1,039 1,559

TSL – 2,3 0.404 248 495 743

TSL – 4,5 0.591 169 339 508

TSL – 6 0.749 134 267 401

TSL – 7 1.919 52 104 156

Non­Standard PTHPs

TSL – 1 0.039 2,586 5,173 7,759

TSL – 2,3 0.053 1,877 3,755 5,632

TSL – 4,5 0.091 1,102 2,205 3,307

TSL – 6 0.147 682 1,365 2,047

TSL – 7 0.206 486 973 1,459

d The scale factors can also be viewed as interpolating values relative to the set of NEMS­BT 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 TSL­3 for standard size PTAC equipment would be

0.224 x 0.10 = 0.022.

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J.3 Regression Smoothing of NEMS­BT Outputs

Even at the selected multiplier levels shown in Table J.1.1, the simulations with

NEMS­BT produces considerable year­to­year 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 year­to­year variation that may or may not be spurious results

from the model solution process.

To reduce the potential effect of numerical noise from NEMS­BT 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:

2 Y(T) = a1 x T + a2 x T + 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, NEMS­BT 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, however, for at least 5 individual

years there are rather large deviations from the trend regression line. In several cases, the

NEMS­BT simulation indicates that the overall downward trend is reversed for periods as long

as 2 years.

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 plants

is very apparent from the graph. The approach in this analysis is to abstract these very shortterm deviations from what appears to be a stable long­term 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.

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Total Generation

­16

­14

­12

­10

­8

­6

­4

­2

0

2

2010 2015 2020 2025 2030

Difference (GW)

NEMS­BT

Fitted

Fossil Steam

­10

­9

­8

­7

­6

­5

­4

­3

­2

­1

0

2010 2015 2020 2025 2030

Difference (GW)

NEMS­BT

Fitted

Combined Cycle

­3.5

­3

­2.5

­2

­1.5

­1

­0.5

0

0.5

2010 2015 2020 2025 2030

Difference (GW)NEMS­BT

Fitted

Combustion Turbine

­8

­7

­6

­5

­4

­3

­2

­1

0

1

2010 2015 2020 2025 2030

Difference (GW)

NEMS­BT

Fitted

Figure J.3.1 Example of Regression Smoothing Fits for Fossil­Fired and Total Installed

Capacity (200X case for PTHP).

J.4 Estimation of Interpolating Functions from Savings Multipliers

The development of utility and environmental impacts focused on specific years from the

NEMS­BT simulations: 2015, 2020, 2025 and 2030. For each output variable (e.g., coal­fired

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 y­intercept of this regression is forced through

the origin. This restriction ensures that the predicted value of a NEMS­BT output variable is

zero when the savings multiplier is zero. Predicted values for non­zero 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 x­axis 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 NEMS­BT 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

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Total Generation

­40

­35

­30

­25

­20

­15

­10

­5

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (TWh)

Coal

­40

­35

­30

­25

­20

­15

­10

­5

0

0 50 100 150 200 250 300 350

Saving Multiplier

Difference(TWh)

Natural Gas

­16

­14

­12

­10

­8

­6

­4

­2

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (TWh)

Nuclear

0

5

10

15

20

25

0 100 200 300 400

Savings Multiplier

Difference (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 coal, the response at the 200X 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 NEMS­BT 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 yields a

decrement of 0.038 TWh in 2020, the savings multiplier would be calculated as

0.5 (= 0.038/.076). For total generation, the estimated response coefficient is ­0.115 (e.g., the

slope of regression line in the top left panel Figure J.4.1). Thus, the estimated impact on total

generation in 2025 from this specific trial standard level would be 0.5 x ­0.115 = ­0.0575 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.

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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 NOx, 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 five­year 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 y­axis is held constant

for each of the plots and so the clockwise rotation of the slopes across the years 2015 through

2030 reflects the increasing reduction in emissions over selected years.

Carbon Dioxide Emissions (2015)

­50

­40

­30

­20

­10

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (MMT­CE)

Carbon Dioxide Emissions (2020)

­50

­40

­30

­20

­10

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (MMT­CE)

Carbon Dioxide Emissions (2025)

­50

­40

­30

­20

­10

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (MMT­CE)

Carbon Dioxide Emissions (2030)

­50

­40

­30

­20

­10

0

0 50 100 150 200 250 300 350

Savings Multiplier

Difference (MMT­CE)

Figure J.5.1 Response (Interpolating) Functions for Carbon Dioxide, PTHP Case, for Years

2015, 2020, 2025 and 2030.

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REFERENCES

1. U.S. Department of Energy. Energy Information Administration. National Energy Modeling

System: An Overview 2003. (DOE/EIA­0581(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 2007, February 2007. Washington, D.C. DOE/EIA­0383(2007).

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