APPENDIX 14A. INTERPOLATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS­BT OUTPUT

LIST OF TABLES

Table 14A.1 Set of Multipliers for Various IRL Standards........................................... 14A­1

Table 14A.2 Set of Multipliers for Various GSFL Standards ....................................... 14A­2

LIST OF FIGURES

Figure 14A.1 An Example of Interpolation of a Trial Standard Level: Difference in

Total Generating Capacity ........................................................................ 14A­3

Figure 14A.2 An Example of Estimates Based on Regression Results of a Sample

Trial Standard Level: Difference in Total Generating Capacity............... 14A­4

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APPENDIX 14A. INTERPOLATION OF UTILITY AND ENVIRONMENTAL

RESULTS FROM NEMS­BT OUTPUT

The effects of proposed incandescent reflector lamp (IRL) and general service

fluorescence lamp (GSFL) efficacy standards on the electric power industry were analyzed using

a variant of the U.S. DOE/EIA National Energy Modeling System (NEMS) called NEMS­BT,

together with some exogenous calculations. Because the relative size of the energy savings

being implemented in NEMS­BT was, in general, too small to be reliably estimated in the

context of the whole electricity sector, adjustments to the NEMS­BT runs were necessary.

To run a simulation in NEMS­BT, the Residential Demand Module, Commercial

Demand Module and Industrial Demand Modules electric lighting end use is reduced annually

according to the energy savings estimated by the National Energy Savings model (see Chapter

13) for a given trial standard level. These energy savings varied over time.

The magnitude of the energy decrement that would be required for NEMS­BT to produce

stable results safely out of the range of numerical noise made it necessary, in both the utility

analysis and environmental assessment, to estimate results in the range of the standard levels

effects using interpolation. Interpolated values are derived from a series of higher decrement

simulations based on the standard levels. The standard levels for the IRL and GSFL analysis

were modeled separately under two technology penetration scenarios.

To preserve the pattern of energy savings over time for a trial standard level, savings in

each year were multiplied by the same “scaling” factor. This factor varies between standards

because the magnitude of the savings changes. An appropriate set of multipliers was chosen to

augment the savings to a magnitude that produces more stable results. Using professional

judgement, sets of three multipliers were selected for each of the modeled trial standard levels as

shown in Table 14A.1 for IRL and Table 14A.2 for GSFL.

Table 14A.1 Set of Multipliers for Various IRL Standards

IRL Existing Technologies, Shift Product Substitution Scenario

Trial Standard Level 39., 79., 118.

Trial Standard Level 15., 30., 44.

Trial Standard Level 8., 16., 25.

Trial Standard Level 7., 13., 20.

Trial Standard Level 6., 12., 18.

IRL Emerging Technologies Roll­up No Product Substitution Scenario

Trial Standard Level 72., 143., 215.

Trial Standard Level 31., 61., 92.

Trial Standard Level 16., 32., 48.

Trial Standard Level 13., 26., 39.

Trial Standard Level 11., 22., 33.

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Table 14A.2 Set of Multipliers for Various GSFL Standards

GSFL Exisiting Technologies, Shift, High Lighting Expertise

Trial Standard Level 3.6, 7.2, 10.8

Trial Standard Level 3.4, 6.8, 10.2

Trial Standard Level 1.9, 3.8, 5.7

Trial Standard Level 1.0, 2.0, 3.1

Trial Standard Level .9, 1.9, 2.8

GSFL Emerging Tech., Roll up, Market Segment Based Lighting Expertise

Trial Standard Level 10.2, 20.3, 30.5

Trial Standard Level 6.7, 13.3, 20.0

Trial Standard Level 3.9, 7.8, 11.7

Trial Standard Level 2.5, 5.1, 7.6

Trial Standard Level 2.0, 4.1, 6.1

The output for electricity generation and capacity by fuel type for each of the scaled

model runs (e.g., 3.6, 7.9, 10.8 times the standard level) is then regressed, with the y­intercept

forced through the origin, and the actual standard level forecast is interpolated along this

regression line. The linear regression is forced through the origin because a zero change must be

the case with no standard in place and because the target points of interpolation are close to the

origin (i.e., at low energy decrements).

Figure 14A.1 shows an example of the interpolation approach for a proposed trial

standard level. The magnitude of the energy savings multiplier is plotted on the x­axis against

the reduction in total installed generating capacity for the years 2020, 2025 and 2030, as shown

by the various plotted lines. In general, results for the various NEMS­BT runs are reasonably

stable and linear. Using these interpolation techniques, the results of the NEMS­BT model runs

have been used to estimate the annual values of selected variables for each of the trial standard

levels. Figure 14A.2 shows estimates of total generating capacity reductions associated with a

sample trial standard level for the years 2012 to 2030 (the last year output from NEMS­BT).

As was discussed more fully in Chapter 16 of the TSD, because the courts vacated CAIR

and CAMR, the 2008 version of NEMS­BT could not be used directly to estimate emissions

impacts for NOX and Hg. Instead, DOE established a range of NOX reductions due to standards.

DOE’s high estimate was based on the use of a nationwide NOX emission rate for electrical

generation. DOE derived a current NOX emission rate for the power sector based on data from

the Annual Energy Outlook 2008 (AEO2008). DOE based the emission rate on the tons of NOX

emitted per TWh of electricity generated in the year 2006. For 2006, the NOX emission rate was

0.764 kt/TWh (0.842 thousand short tons/TWh). DOE’s low estimate was based on the use of an

emission rate for new combined­cycle gas plants as provided in the NEMS­BT. This emission

rate equals 0.0310 kt/TWh (0.0341 thousand short tons/TWh) and represents the lowest emission

rate of fossil­fuel based generation that might be displaced under standards. To estimate the

reduction in NOX emissions from the power sector, DOE multiplied these emission rates by the

reduction in electricity generation due to the standards considered as determined by the utility

impact analysis (see Chapter 14, Utility Impact Analysis). The estimates of the total reduction in

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electricity generation was developed using the interpolation technique described above and

illustrated in Figure 14A.1.

DOE estimated the physical quantity changes in Hg emissions associated with the energy

conservation standard. As opposed to using the NEMS­BT model, DOE established a range of

Hg reductions due to standards. DOE’s high estimate used an Hg emission rate based on the

AEO2008. Because virtually all Hg emitted from electricity generation is from coal­fired power

plants, DOE based the emission rate from the tons of Hg emitted per TWh of coal­generated

electricity. DOE based the emission rate on the average value reported in the AEO2008 for the

year 2006. This emission rate is 0.0230 metric tons per TWh (0.0253 short tons/TWh). DOE’s

low estimate was based on the use of an emission rate for new combined­cycle gas plants as

provided in the NEMS­BT. The emission rate for this generation technology is 0.000 tons per

TWh. To estimate the reduction in Hg emissions from the power sector, DOE multiplied the low

and high emission rates by the reduction in coal­generated electricity due to the standards

considered as determined in the utility impact analysis (see Chapter 14, Utility Impact Analysis).

Again, the estimates of the reduction in coal electricity generation was developed using the

interpolation technique described above and illustrated in Figure 14A.1

Figure 14A.1 An Example of Interpolation of a Trial Standard Level: Difference in

Total Generating Capacity

Regression of Scaled Results

Total Generating Capacity Reductions

y = ­15.681x

y = ­12.667x

y = ­8.6159x

(100)

(90)

(80)

(70)

(60)

(50)

(40)

(30)

(20)

(10)

­

­ 1.0 2.0 3.0 4.0 5.0 6.0

Scaling Factor

GW Savings

2025 2020 2030 Linear (2025) Linear (2020) Linear (2030)

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Figure 14A.2 An Example of Estimates Based on Regression Results of a Sample

Trial Standard Level: Difference in Total Generating Capacity

Estimates of Savings Based on Regression for Total Generating Capacity

(18)

(16)

(14)

(12)

(10)

(8)

(6)

(4)

(2)

­

2012201320142015201620172018201920202021202220232024202520262027202820292030

GW Savings

The highlighted results for the years 2020, 2025 and 2030 were directly interpolated from the

regressions shown in Figure 14A.1

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