14A-i

INTERPOLATION OF UTILITY AND ENVIRONMENTAL RESULTS FROM 

NEMS-BT OUTPUT 

LIST OF TABLES 

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

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

LIST OF FIGURE 

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

Total Generating Capacity ........................................................................ 14A-3 

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

Trial Standard Level: Difference in Total Generating Capacity............... 14A-4 
APPENDIX 14A. INTERPOLATION OF UTILITY AND ENVIRONMENTAL 

RESULTS FROM NEMS-BT OUTPUT 

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

fluorescence lamp (GSFL) efficiency 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 NEMS-BT was, in general, too small to be reliably estimated in the 

context of the whole electricity sector, adjustments to the NEMS-BT runs were necessary. 

 To run a simulation in NEMS-BT, 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 NEMS-BT 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 

judgment, 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, R-CFL Substitution

Trial Standard Level 1 30, 61, 91

Trial Standard Level 2 13, 26, 39

Trial Standard Level 3 7, 15, 22

Trial Standard Level 4 6, 12, 17

Trial Standard Level 5 5, 10, 15

IRL Emerging Technologies, Rollup, BR Lamp Substitution

Trial Standard Level 1 90, 180, 269

Trial Standard Level 2 38, 75, 113

Trial Standard Level 3 18, 37, 55

Trial Standard Level 4 16, 32, 49

Trial Standard Level 5 14, 27, 41

14A-1
Table 14A.2 Set of Multipliers for Various GSFL Standards 

GSFL Existing Technologies, Shift, High Lighting Expertise

Trial Standard Level 1 5.4, 10.7, 16.1

Trial Standard Level 2 4.9, 9.8, 14.6

Trial Standard Level 3 2.1, 4.3, 6.4

Trial Standard Level 4 1.3, 2.6, 3.8

Trial Standard Level 5 1.0, 2.1, 3.1

GSFL Emerging Technologies, Roll Up, Market Segment Based Lighting Expertise

Trial Standard Level 1 10.5, 21.0, 31.5

Trial Standard Level 2 7.6, 15.2, 22.8

Trial Standard Level 3 4.5, 9.0, 13.5

Trial Standard Level 4 3.5, 7.1, 10.6

Trial Standard Level 5 2.5, 5.1, 7.6

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

model runs (e.g., 5.4, 10.7, 16.1 times the standard level) is then regressed, with the y-intercept 

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 x-axis 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 NEMS-BT runs are reasonably 

stable and linear. Using these interpolation techniques, the results of the NEMS-BT 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 NEMS-BT). 

 As was discussed more fully in Chapter 16 of the TSD, NEMS-BT was not used directly 

to estimate emissions impacts for mercury (Hg). Instead, DOE established a range of Hg 

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

historical emissions rate. Because virtually all Hg emitted from electricity generation is from 

coal-fired power plants, DOE based the emission rate from the tons of Hg emitted per TWh of 

coal-generated electricity and used 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 combined-cycle gas plants as provided in the 

NEMS-BT. The emission rate for this generation technology is 0.000 tons per TWh. To estimate 

the high end reduction in Hg emissions from the power sector, DOE multiplied the high emission 

rate by the reduction in coal-generated electricity due to the standards considered as determined 

in the utility impact analysis (see Chapter 14, Utility Impact Analysis). Again, the estimates of 

14A-2
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)

14A-3
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 

14A-4