10

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- i APPENDIX 10

- C. FULL FUEL CYCLE MULTIPLIE RS

TABLE OF CO NTENTS

10

- C.1 METHODOLOGY

................................ ................................ .............................. 10

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- 1

LIST OF TABLES

Table 10

- C.1.1 Full Fuel Cycle Multipliers for the AEO2011 Forecast Period

............... 10

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- 310

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- 1 APPENDIX 10

- C. FULL FUEL CYCLE MULT IPLIERS

10

- C.1 METHODOLOGY

To provide one unit of energy to the final consumer, for example, in buildings, vehicles or industrial processes, a variety of fuels are used in upstream activities. Thus, if the point

- of

- use (site) energy demand is reduced by one unit, the economy

- wide demand for energy will be reduced by an additional amount correspon ding to this upstream fuel use. The sum of site energy and upstream energy is called the full

- fuel cycle (FFC) energy. This appendix provides a brief description of the methodology used to calculate FFC savings from the site energy savings that

result from a candidate standard level. The mathematical approach is discussed in Coughlin (2012) 1 , and details on the fuel production chain analysis are presented in 2 This appendix outlines the steps involved in the calculation, defines the data that are taken from the AEO and used in the calculation, and presents the results of the calculations for electricity, natural gas and

fuel oil.

When all quantities are normalized to the same units, the FFC energy can be represented as the product of the site energy and an F FC multiplier

. The multiplier is defined mathematically

as a function of a set of parameters representing the energy intensity and material losses at each production stage. The se parameters depend only on physical data, i.e. the calculations do not requir e any assumptions about prices or other economic data . Most generally, these p arameter values may vary by geographic region, time, etc . For the calculations used in this analysis, the parameters represent national averages.

Schematically, the steps in the calculation of FFC energy associated with electricity savings are:

1. Assume the site energy savings, denoted S 0 (mWh), are known.

2. Site electricity savings are converted to electricity savings at the power plant, taking into

account the transmission and distribution loss factors. The power plant electricity savings are given by S 1 = tdloss*S 0 , where

• S 1 is the power plant electricity savings (mWh)

• tdloss is the transmission & distribution loss factor a

3. Power plant electricity savings are converted to fuel savings. This conversion depends on a set of parameters a

x where

• x is an index used to indicate fuel type, with x=c for coal, x=g for natural gas, and x=p for petroleum fuels

• a x is the amount of fuel x consumed per MWh of electricity produced at the power plant

• The fuel savings are S 2x = a x S 1 , for each fuel type x

a The values for tdloss are taken from NEMS. The value depends on region and changes slightly over the forecast period. The range of tdloss is 1.07 to 1.09.10

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- 2 The value of a

x over the analysis period is calculated from NEMS output. It depends on the capacity mix by fuel type, and on individual power plant efficie ncies or heat rates, and so varies with region and with time. The higher the penetration of renewables, the

lower the value of a

x . 4. For each fuel type x, an analysis of the fuel production chain determines the amount of energy required to produce one unit of fuel for site consumption. This analysis accounts for all energy sources, including electricity, that are used in fuel production. The consumption of fuel y required to provide one unit of fuel x for site consumption is denoted by the matrix element V xy . 5. The matrix elements V xy , which represent the incremental use of fuel y in the production chain for fuel x, are converted to the matrix elements M xy , which represent the economy wide reduction in demand for fuel y resulting from a one unit reduction in d emand for

fuel x.

6. The equation S 3y = ∑
x M xy S 2x gives the full fuel cycle savings of fuel y.

7. The fuel savings are converted to energy units by multiplying S 3y by the heat content of fuel y, denoted q y . The total FFC energy savings are given by the sum over the index y, so the total is equal to ∑
x q y S 3y

.

In addition to electricity, natural gas and petroleum

- based fuels (primarily fuel oil) are used in buildings. The steps required to calculate the ful l fuel cycle energy use associated with production of gas or fuel oil are essentially identical to the scheme outlined above. The only difference is that the analysis begins at step 3, with the site fuel savings substituted for S 2x

.

For simplicity in app lications, the FFC energy use is summarized as a multiplier μ (mu). This is a dimensionless number that can be applied to the site energy savings to obtain the FFC energy savings. The upstream component of the energy savings is proportional to (1

- μ).

Thi s methodology is completely general and is based on the mathematical definition of the quantity the FFC energy is meant to represent. The supporting numerical calculations of the parameters can be implemented in a variety of ways. As the data required are incomplete, some simplifying assumptions or approximations need to be made (these are explained in detail in 2 ). These will generally have a limited quantitative im pact, but may lead to small differences in the fuel cycle energy use parameters calculated by different authors. The GREET model developed by Argonne National Laboratory 3 is one example of a spreadsheet tool that calculates full fuel cycle energy use, with a focus on vehicle

- fuel systems. For the Department's appliance standards energy savings estimates, the implementation of the FFC calculations has been designed specifically to make use of energy forecast data published in the AEO. These data include time

series of:

1. Domestic production of natural gas by source type, imports of natural gas, and natural gas use by the oil and gas industry

2. Domestic production and imports of petroleum fuels by source type; total refinery inputs, outputs and refinery fuel use

3. Electric generating capacity by fuel type and fuel consumption for power generation

4. Coal use for power generation, by source type and coal quality10

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- 3 5. Fuel heat content for each fuel type

These quantities vary with each year in the AEO forecast period, leadin g to a corresponding variation in estimates of the full fuel cycle energy multipliers. Multipliers are presented in Table 1 for the AEO forecast years 2012 to 2035. To extend the analysis period beyond 2035, the years

2020 to 2035 are used to define a line ar trend, which is then extrapolated to the final year of the analysis period.

For electricity, the site

- to

- source conversion factors are not included in the multiplier

shown in Table 10

- C.1.1 . Hence, this multiplier is applied to the source energy savings. Site

- to

source conversion factors are given in chapter 10.

Table 10

- C.1.1 Full F uel C ycle M ultipliers for the AEO2011 F orecast P eriod

Forecast year Source Energy Savings For Electricity Site Fuel Oil Savings Site Natural Gas Savings

2008 1.056 1.123 1.135

2009 1.058 1.120 1.129

2010 1.061 1.120 1.139

2011 1.060 1.118 1.139

2012 1.060 1.131 1.136

2013 1.059 1.130 1.133

2014 1.059 1.130 1.131

2015 1.059 1.129 1.129

2016 1.058 1.129 1.128

2017 1.058 1.130 1.127

2018 1.057 1.129 1.126

2019 1.057 1.128 1.125

2020 1.056 1.127 1.126

2021 1.055 1.127 1.125

2022 1.055 1.127 1.125

2023 1.055 1.127 1.125

2024 1.054 1.127 1.124

2025 1.054 1.127 1.123

2026 1.053 1.127 1.123

2027 1.053 1.127 1.122

2028 1.054 1.128 1.122

2029 1.054 1.128 1.121

2030 1.055 1.130 1.121

2031 1.055 1.131 1.120

2032 1.055 1.131 1.120

2033 1.055 1.131 1.120

2034 1.055 1.132 1.121

2035 on 1.055 1.132 1.12110

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- 1 REFERENCES

1 Coughlin, Katie. (2012a) “A Mathematical Analysis of Full Fuel Cycle Energy Use.” Energy 37(1), pp. 698

– 708. http:// www.sciencedirect.com/science/article/pii/S0360544211006803.

2 Coughlin, Katie. (2012b) "Calculation of Full Fuel Cycle Multipliers for Energy Use in Buildings". L awrence B erkeley N ational L aboratory, July 2012.

3 Argonne National Laboratory. The Greenh ouse Gases, Regulated Emissions, and Energy Use in Transportation Model. http://greet.es.anl.gov/