8

- G

- i APPENDIX 8

- G. COMPARISON OF MARGIN AL PRICES DERIVED FR OM DEFAULT TARIFFS, TIM E

- OF

- USE TARIFFS AND TIME DEPENDENT VALUATION

TABLE OF CO NTENTS

8

- G.1 INTRODUCTION

................................ ................................ ................................ . 8

- G

- 1 8

- G.2 COMPARISON OF TOU AN D DEFAULT TARIFF MAR GINAL PRICES

..... 8

- G

- 1 8

- G.3 COMPARISON OF DEFAUL T TARIFF, TOU TARIFF S, AND TDV MARGINAL PRICES

................................ ................................ ........................... 8

- G

- 4

LIST OF TABLES

Table 8

- G.2.1 Whole building energy consumption for July (CD is census division)

..... 8

- G

- 2 Table 8

- G.3.1 California Climate Zone assignment for Hot

- Dry Cities

........................... 8

- G

- 5

LIST OF FIGURE S
Figure 8

- G.2.1 Comparison of the effective marginal price for each account

................... 8

- G

- 3 Figure 8

- G.2.2 Effective marginal prices for all accounts, organized by census division

................................ ................................ ................................ ....... 8

- G

- 4 Figure 8

- G.3.1 Comparison of the effective marginal price for hot

- dry region

................. 8

- G

- 6 Figure 8

- G.3.2 Effective default, TOU, and TDV marginal prices for hot

- dry cities

........ 8

- G

- 68

- G

- 1 APPENDIX 8

- G. COMPARISON OF MARGIN AL PRICES DERIVED FROM DEFAULT TARIFFS , TIME

- OF

- USE TARIFFS AND TIME DEPENDENT VALUATION

8

- G.1 INTRODUCTION

There is a concern that the electricity prices used in the life

- cycle cost (LCC) and payback period (PBP) analysis do not reflect the real cost of serving system

- peak coincident loads such as air

- conditioning. There have been suggestions that basing electricity costs on time

of

- use ( TOU) tariffs would provide a more realistic picture of the real value of reducing peak

coincident electricity use. For the hot

- dry region of the U.S., there have also been suggestions that time dependent valuation (TDV) would provide an even more realistic depiction of the real value of reducing peak

- coincident electricity use than either default (i.e., non

- TOU) or TOU tariffs. To investigate this issue, the DOE conducted an analysis to compare prices derived from def ault (i.e. non

- TOU) tariffs and TOU tari ffs . Further, DOE conducted an analysis to compare prices derived from default tariffs, TOU tariffs, and TDV specifically for the hot

- dry region . The tariff data were collected as part of the Tariff Analysis Project (TAP) database update (see appendix 8

- B )

.
8

- G.2 COMPARISON OF TOU AN D DEFAULT TARIFF MAR GINAL PRICES Many utilities offer optional TOU tariffs, but for the moment there are no utilities which have mandatory TOU tariffs for residential customers. The Federal Energy Regulatory Commission (FERC) 2008 s taff report on demand response provides a figure (Figure III

- 15) that indicates approximately 1.2 million residential customers are on TOU tariffs. 1 Based on the total residential consumer count from the Energy Information Administration ( EIA ) Form 861 (20 07), 2 this represents less than 1 percent of all consumers. The penetration of TOU rates is thus still very low. For this reason, the Department does not include TOU tariffs in the sample used to develop electricity prices for the LCC.
Optional TOU tarif f are included in the TAP database for all utilities that offer them. Currently, 48 of the 102 utilities in the sample offer TOU rates. These optional TOU tariffs are used here to determine whether the difference in electricity prices for TOU vs. non

- TOU t ariffs is significant for this rule

- making. This determination can only be made for current rate structures; it may be repeated in the future as rate structures continue to evolve.
Each utility defines the hours associated with TOU periods (on

- peak, off

- peak and shoulder) differently. To correctly calculate electricity bills for TOU tariffs therefore requires hourly whole

- building electricity consumption data. For this analysis, these data were obtained from EnergyPlus building simulations. 3 The simulatio ns use a prototype residential single

- family detached home, with a central air conditioning (CAC) system and gas furnace, sited in twenty

two different weather locations. Two sets of simulations were performed, with CAC efficiencies of 13 SEER and 16 SEER. Both assume a single

- speed air conditioner.8

- G

- 2 As in the LCC, a set of customer accounts are defined by pairing each residential building with all utilities in its region. For the analysis presented here, regions are defined as census divisions. For each building

- utility pair, monthly utility bills are calculated using both the default tariff and the TOU tariff (utilities that do not offer TOU tariffs are not included in this analysis). For each account, the electricity cost savings are defined as the difference between the bill in the 13 SEER case and the bill in the 16 SEER case. The energy savings are defined similarly. The effective marginal electricity price is defined as the ratio of the bill savings to the energy savings.
The output of this a nalysis is summarized in Table 8

- G .2.1 and Figures 8

- G .2.1 and 8

- G .2. 2. Seasonal rates can be represented by looking at data for January and July. For the month of January the energy savings between 13 and 16 SEER are essentially zero, so only data for July are presented. Table 8

- G .2.1 shows, for each loca tion, the monthly energy use in July in the 13 and 16 SEER cases; the energy use is for the whole building, but the difference between the two is due to CAC only. The energy savings are also given as a percentage of the 13 SEER whole building load.

Table 8

- G.2.1 Whole building energy consumption for July (CD is census division)

City State CD kWh SEER 13 kWh SEER 16 kWh Savings Boston MA 1 1177 1064 9.6% New York NY 2 1432 1282 10.5% Chicago IL 3 1427 1279 10.4% Kansas City MO 4 986 933 5.3% Minneapolis MN 4 950 913 4.0% Atlanta GA 5 1340 1184 11.6% Miami FL 5 1234 1095 11.3% Sterling VA 5 1202 1084 9.8% Dallas TX 7 1460 1283 12.1% El Paso TX 7 1200 1086 9.5% New Orleans LA 7 1364 1210 11.3% San Antonio TX 7 1292 1156 10.6% Albuquerque NM 8 1207 1078 10.7% Denver CO 8 953 893 6.3% Las Vegas NV 8 1721 1468 14.7% Phoenix AZ 8 2254 1872 16.9% Tucson AZ 8 1605 1381 14.0% Fresno CA 9 1529 1336 12.6% Los Angeles CA 9 892 853 4.4% Sacramento CA 9 1156 1053 8.9% San Francisco CA 9 771 761 1.3% Seattle WA 9 805 770 4.4%
Figures 8

- G .2.1 and 8

- G .2. 2 summarize the output of the price calculations. Figure 8

- G .2. 1 is a scatter plot of the effective marginal price for the TOU tariff vs. the effective marginal8

- G

- 3 price for the default tariff. Each point represents one account, i.e. one building

- utility pair. A diagonal line is included in the plot for reference. The da ta show that there is no coherent pattern of higher prices for TOU tariffs; in fact there are cases where the effective price is substantially lower than for the default tariff. This pattern is confirmed in Figure 8

- G .2. 2, which shows the default and TOU p rices separately. The two sets of prices have been organized by census division for this plot. Figure 8

- G

. 2. 2 shows that the spread of TOU and default prices is comparable, with the exception of census division 4 (West North Central) where the TOU July pri ce is substantially higher than the default price.
These data show that, currently, there is no significant difference on average between TOU and default tariffs for the electricity costs used in the LCC. This may be due to several factors. For current tariffs, the commodity price (cents per kWh) in different TOU periods is often comparable to the default tariff price, and if the on

- peak prices are higher the off

- peak or shoulder prices are typically lower. The distribution of energy savings across the d ifferent TOU periods also has a strong impact on the effective marginal price. For residential cooling there may be significant appliance use outside the utility’s peak hours (which tend to be week

- day afternoons), which will moderate the impact of higher on
- peak prices.

Figure 8

- G.2.1 Comparison of the effective marginal price for each account 0 5 10 15 20 25 30 35 40

0 10 20 30 40 Default price cents/kWhTOU price cents/kWh July y=x8

- G

- 4 Figure 8

- G.2.2 Effective marginal prices for all accounts, organized by census division

8

- G.3 COMPARISON OF DEFAUL T TARIFF , TOU TARIFFS, AND T DV MARGINAL PRICES
The California Energy Commission (CEC) has developed TDV to value the energy for California’s building energy performance standards. 4 Under TDV, the value of electricity differs depending on time

- of

- use (hourly, daily, seasonal), and the value of natural gas differs depending on season. TDV is based on the cost for utilities to provid e the energy at different times and is believed to provide a more realistic depiction of the real value of reducing peak

- coincident electricity use.

E fficiency requirements that would improve the EER of a central air condit ioner in the hot

- dry region are under consideration by DOE because EER is believed to improve the performance of the equipment at peak conditions when the equipment is operating at its full capacity . Because TOU

- based and margi nal prices and TDV of electricity may be more representative of the true cost of electricity supply at peak

- coincident conditions than marginal prices derived from default tariffs, DOE compared the three types of methods of valuing electricity for the hot

- dry region.
To investigate the impact of the TDV of electricity in the hot

- dry region, DOE used CEC’s TDV method and applied it to the building energy simulations that were performed for the above eight cities that reside in the hot

- dry region ( Albuque rque , Las Vegas, Phoenix, Tucson, Fresno, Los Angeles, Sacramento, and San Francisco). A TDV of electricity has been 0 5 10 15 20 25 30 35 40

1 2 3 4 5 6 7 8 9 10 Census DivisionPrice cents/kWh July default July TOU8

- G

- 5 generated by the CEC for each of California’s 16 climate zones. For the four cities residing in California, each was matched to the TDV s pecific to its climate zone. For the four cities outside of California, the California climate zone with weather most similar to each city’s climate was used. Table 8

- G.3.1 summarizes the California cli mate zones assigned to each of the hot

- dry cities

.
Table 8

- G.3.1 California Climate Zone assignment for Hot

- Dry Cities City State California Climate Zone Albuquerque NM 12 Las Vegas NV 15 Phoenix AZ 15 Tucson AZ 15 Fresno CA 13 Los Angeles CA 8 Sacramento CA 12 San Francisco CA 3
Figures 8

- G.3.1 and 8

- G .3.2 summarize the output of the price calculations fo r the hot

dry region. Figure 8

- G .3.1 is a scatter plot of the effective marginal price for the TOU tariff vs. the effective marginal price for the default tariff and the effective marginal price for the TDV of electricity vs. default tariff marginal price. A diagonal line is included in the plot for reference. The data show that prices for TOU tariffs for TDV are lower than for the default tariff. This pattern is confirmed in Figu re 8

- G .3.2, which shows the default, TOU, and TDV

- based prices separately for each of the eight hot

- dry cities. Only Los Angeles has a TDV

- based marginal price equal to the price derived from the default tariff.
These data show that, TOU

- based and TDV

- based marginal prices are not significantly different , and in fact lower, than the marginal prices derived from default tariffs. Therefore, DOE determined that they would not have a significant effect on the economic justification of more

stringent efficiency standards.8

- G

- 6 Figure 8

- G.3.1 Comparison of the effective marginal price for hot

- dry region

Figure 8

- G.3.2 Effective default, TOU, and TDV marginal prices for hot

- dry cities 0 2 4 6 8 10 12 14 16 18 20

0 5 10 15 20 Default price cents/kWhTOU price or TDV price cents/kWh TOU y=x TDV

0 5 10 15 20

Albuquerque Las_Vegas Phoenix Tucson Fresno Los_Angeles Sacramento San_Francisco Census DivisionPrice cents/kWh July default July TOU July TDV8

- G

- 7 REFERENCES

1 FERC . Assessment of Demand Response and Advanced Metering. Staff Report, Federal Energy Regulatory Commission , December 2008. Available at: http://www.ferc.gov/legal/staff

- reports/12

- 08

- demand

- response.pdf

.
2 EIA. Energy Informati on Agency Annual Electric Power Industry Database Form 861 , 2007. Available at: http://www.eia.doe.gov/cneaf/electricity/page/eia861.html

.
3 U. S. Department of Energy, EnergyPlus En ergy Simulation Software . Available at: http://apps1.eere.energy.gov/buildings/energyplus/

.
4 California Energy Commission, Time

- Dependent Valuation (TDV) . Available at: http://www.energy.ca.gov/title24/2005standards/archive/rulemaking/documents/tdv/index.ht ml

.