METHODOLOGY FOR ENERGY EFFICIENCY

Total primary energy supply (TPES)

(in terajoules [TJ]) Production plus net imports minus international marine and aviation bunkers plus/minus stock changes (IEA definition).

Data sources: Energy balances from IEA, supplemented by United Nations Statistics Division (UNSD) for countries not covered by the IEA

Gross domestic product (GDP) (in 2011 purchasing power parity [PPP]

U.S. dollars)

Sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. GDP is measured at PPP at constant 2011 U.S. dollars.

Data source: World Bank’s World Development Indicators (WDI) Energy intensity of primary energy

supply (in MJ per 2011 PPP $) Energy intensity of TPES = Primary energy supply (MJ) GDP (2011 PPP $)

Ratio between energy supply and GDP measured at PPP. Energy intensity is an imperfect proxy for energy efficiency. It indicates how much energy is used to produce one unit of economic output. A lower ratio indicates that less energy is used to produce one unit of economic output.

Rate of primary energy intensity improvement (%)

CAGR of TPES = PEI_t2 – 1 (%) PEI_t1

1 (t2 – t1)

where,

PEI_t1 : primary energy intensity in year t1 PEI_t2 : primary energy intensity in year t2

Compound annual growth rate (CAGR) of primary energy intensity between two years. Represents the average annual growth rate during the period. Negative values represent improvements in energy intensity (less energy is used to produce one unit of economic output), while positive numbers indicate declining energy intensity (more energy is used to produce one unit of economic output).

Total final energy consumption (TFEC)

(in TJ) Sum of energy consumption by the different end-use sectors, excluding nonenergy uses of fuels. TFEC is broken down into energy demand in the following sectors: industry, transport, residential, services, agriculture, and others. It excludes international marine and aviation bunkers, except at world level where it is included in the transport sector.

Data sources: Energy balances from IEA, supplemented by UNSD for countries not covered by IEA Energy intensity of total final energy

consumption (in MJ per 2011 PPP $) Energy intensity of TFEC = Final energy consumption (MJ) GDP (2011 PPP $)

A ratio between final energy consumption and GDP measured at PPP. Energy intensity is an indication of how much energy is used to produce one unit of economic output. A lower ratio indicates that less energy is used to produce one unit of economic output.

Rate of final energy intensity improvement (in %)

CAGR of TFEC = FEI_t2 – 1 (%) FEI_t1

1 (t2 – t1)

where,

FEI_t1: final energy intensity in year t1 FEI_t2: final energy intensity in year t2

CAGR of final energy intensity between two years. Represents the average annual growth rate during the period. Negative values represent improvements in energy intensity (less energy is used to produce one unit of economic output), while positive numbers indicate declining energy intensity (more energy is used to produce one unit of economic output).

Energy intensity of industrial sector

(in MJ per 2011 PPP $) Industrial energy intensity = Industrial energy consumption (MJ) Industrial value added (2011 PPP $)

Ratio between energy consumption in industry (including energy industry own use) and industry sector value added measured at PPP.

Data sources: Energy balances from IEA and WDI, supplemented by UNSD for countries not covered by IEA or WDI.

Energy intensity of agricultural sector

(in MJ per 2011 PPP $) Agriculture energy intensity = Agriculture energy consumption (MJ) Agriculture value added (2011 PPP $)

Ratio between energy consumption in agriculture (including forestry and fishing) and agricultural sector value added measured at PPP.

Data sources: Energy balances from IEA and WDI, supplemented by UNSD for countries not covered by IEA or WDI.

Energy intensity of service sector

(in MJ per 2011 PPP $) Services energy intensity =Services energy consumption (MJ) Services value added (2011 PPP $)

Ratio between energy consumption in services (including commercial and public services) and services sector value added measured at PPP.

Data sources: Energy balances from IEA and WDI, supplemented by UNSD for countries not covered by IEA or WDI.

Energy intensity of passenger and freight transport (in MJ/passenger-km and MJ/ton-km)

Passenger energy intensity =Passenger energy consumption (MJ) Passenger activity (passenger-km)

Freight energy intensity = Freight energy consumption (MJ) Freight activity (ton-km)

Ratio between passenger travel and freight energy consumption, and transportation activity measured in passenger-kilometers and ton-kilometers, respectively.

Data source: IEA Mobility Model Energy intensity of residential sector

(in GJ/population) Residential energy intensity = Residential energy consumption (GJ) Population

Ratio between energy consumption in residential sector and population.

Data sources: Energy balances from IEA, supplemented by UNSD for countries not covered by IEA, and UN Population Division.

74 • SUSTAINABLE ENERGY FOR ALL GLOBAL TRACKING FRAMEWORK  Progress toward Sustainable Energy 2017

Logarithmic mean Divisia index (LMDI)

decomposition of energy consumption D_tot = E^T = D_act · D_str · D_eff E⁰

where the ratio change of energy consumption from year 0 to year T, E^T/E⁰, is decomposed to give the activity, structure, and efficiency indexes, D_act, D_str, and D_eff, respectively.

Assume that total energy consumption in a specific sector is the sum of consumption in n different subsectors and define the following variables for a certain period:

E = total final energy consumption in the sector E_i = final energy consumption in subsector i

Q = total activity level of the sector (value added, population, passenger-km, ton-km for industry, agriculture, and services; residential; passenger travel; and freight transport, respectively)

Q_i = activity level of subsector i

S_i = activity share of subsector i (= Q_i /Q) I = aggregate energy intensity (= E/Q) I_i = energy intensity of subsector i (= E_i/Q_i)

Based on the data for year t–1 and year t, the decomposition formulae are given by:

D_act = exp

∑

i w_i ln QQ^t–1t

D_str = exp

∑

i w_i ln S_i^t S_i^t–1 D_eff = exp

∑

i w_i ln I_i^t

I_i^t–1 w_i =

∑

i

(S_i^t – S_i^t–1)/(lnE_i^t – S_i^t–1) (E^t – E^t–1)/(lnE^t – E^t–1)

The activity, structure, and intensity decomposition indexes, setting a certain year as the baseline year (for example, 2010), are derived by calculating the product of the index of each category in previous years as of 2010.

Composite economy-wide decomposition index

The LMDI chaining analysis was carried out by decomposing by factor then aggregating by sector. Two independent index decomposition analysis results for the residential, transport, and other sectors (agriculture, industry, and services) were then aggregated to derive the economy-wide decomposition index:

(D_tot)_e–w = exp

(∑

i w_j ln(D_eff)_j

)

Where subscript j denotes the sectors to be aggregated, and D_eff results from the formula above.

Data sources: Energy balances from IEA and WDI, supplemented by UNSD for countries not covered by IEA or WDI, UN Population Division, and IEA’s Mobility Model.

Avoided energy demand (EJ)

∆E =

∑

i wln I_i^T I_i⁰ where

w = (E_i^T – E_i⁰) (lnE_i^T – lnE_i⁰)

∆E= avoided energy demand, or energy savings between two years I_i^T = energy intensity in year T in subsector i

Avoided energy demand (or energy saved) was calculated year-to-year (i.e., 2012–13 and 2013–14) using two approaches: (a) bottom-up, based on sector energy intensities, and (b) top-down, based on country-level energy intensity. Thus, for example, avoided energy at country-level in 2013 was calculated as:

Avoided energy in 2013 =

(E²⁰¹³ – E²⁰¹²)/(ln E²⁰¹³ – ln E²⁰¹²) * (ln I²⁰¹³ – ln I²⁰¹²) where

E²⁰¹², E²⁰¹³ = total final energy consumption in years 2012 and 2013 I²⁰¹², I²⁰¹³ = aggregate energy intensity in years 2012 and 2013

A negative value means a reduced energy use due to energy intensity reduction.

Data sources: Energy balances from IEA and WDI, supplemented by UNSD for countries not covered by IEA or WDI, UN Population Division, and IEA’s Mobility Model.

Thermal efficiency of power generation

(%) Efficiency_f = Output_f (%)

Input_f where

Efficiency_f = thermal efficiency of power generation with fuel f in main activity producer electricity plants Output_f = power output with fuel f in main activity producer electricity plants

Input_f = energy input of fuel f in main activity producer electricity plants Data source: Energy balances from IEA

Power transmission and distribution

(T&D) losses (%) Power T&D losses = Electricity losses (%)

(Electricity output main + Electricity output CHP + Electricity imports) where

Electricity losses = electricity transmission and distribution losses

Electricity output main = electricity output from main activity producer electricity plants Electricity output CHP = electricity output from combined heat and power plants Data source: Energy balances from IEA

Natural gas T&D losses (%)

Gas T&D losses = Natural gas losses (%) Natural gas supply Data source: Energy balances from IEA

76 • SUSTAINABLE ENERGY FOR ALL GLOBAL TRACKING FRAMEWORK  Progress toward Sustainable Energy 2017

NOTES

1. Primary energy intensity is the ratio of total primary energy supply (TPES) to gross domestic product (GDP), measured at purchasing power parity (PPP) in constant 2011 U.S. dollars.

2. Avoided energy is calculated using 2012 and 2013 as base years (annex 4.1).

3. The Global Tracking Framework (GTF) uses energy intensity as an imperfect proxy indicator to measure energy efficiency improvements. For a discussion on the limitations of this indicator, please see previous GTF editions (World Bank and IEA 2013; 2015).

4. Revisions of underlying statistical data and methodological improve-ments explain the slight changes in historical growth rates from previous GTF editions. The SEforALL objective of 2.6% improvement in energy intensity in 2010–30 remains the same, however.

5. In 2014, fossil fuels accounted for two-thirds of the electricity generation mix. Coal had the largest share at 40.8%, followed by natural gas at 21.6%. According to IEA projections, the share of fossil fuels decreases to 62% by 2040 in the Current Policies Scenario, and to 52% under the New Policies Scenario, due primarily to the increase in the share of re-newable energy generation. Only under the 450 Scenario does this share fall significantly, to 24% (IEA 2016b).

6. This calculation considers main activity producer electricity plants only.

7. Self-use of coal refers to increased energy use to clean the flue gas in coal-fired generation plants (for example, in selective catalytic reduc-tion, fabric filtrareduc-tion, and flue gas desulphurization). In future, additional efficiency reduction (and increased energy own-use) may result from the adoption of carbon capture and storage technologies.

8. Losses are calculated as a percentage of supply (see annex 4.1).

9. The methodology to calculate gas losses is explained in annex 4.1.

10. Income groups are defined in annex 2.1 in chapter 2.

11. Changes from earlier GTF reports are due to revisions in the underlying data and to countries moving between income groups, reflecting changes in their gross national income per capita.

12. In 2014, China accounted for 53% of GDP and 64% of TPES of upper- middle-income economies.

13. The base years for calculating energy savings are 2012 and 2013. Savings were calculated using a top-down approach (for countries and regions), and an approximate bottom-up approach for sector savings, giving simi-lar global savings of 11.83 EJ and 12.04 EJ, respectively (annex 4.1).

14. Savings in this box describe analysis from the IEA’s Energy Efficiency Market Report 2016 and are not comparable to the savings estimate of 12 EJ in this chapter (IEA 2016a). The IEA used 2000 as the base year and savings stem from an in-depth sectoral decomposition, while those in the rest of this chapter have base years of 2012 and 2013 and follow a different methodology (see annex 4.1).

15. See the list of IEA member countries at https://www.iea.org/countries /membercountries/.

16. Because of the lack of end-use data, the analysis could only capture struc-tural changes among industry, agriculture, and services. The results reflect the relatively stable sectoral shares in value added at global level throughout the historical reference period of 1990–2010 and the two tracking periods (2010–12 and 2012–14). Changes in the shares in value added by country income groups, however, have been significant, especially in industry and services, where the long-term declining share of high-income economies has been largely due to the increase in upper- middle-income economies.

17. Detailed analysis of sector structure effects in IEA countries can be found in IEA’s Energy Efficiency Market Reports (2013; 2014a; 2015a; 2016a).

18. Transport intensities are the result of modeling, based on 5-year intervals, and are thus graphed separately.

19. The following activity drivers were used in each sector: value added (industry, agriculture, services), passenger-km and ton-km (transport), and population (residential). See annex 4.1.

20. The IEA counts investment in energy efficiency as the additional cost of an “energy efficient good” relative to an “average efficiency good.”

In effect, this efficiency premium is the additional investment required to drive efficiency improvements and subsequent energy savings. The efficiency premium is calculated in different ways for the sectors.

21. See the IEA Policies and Measures database (www.iea.org/policiesand measures) and the World Bank RISE database (rise.worldbank.org).

22. Revisions to TPES and GDP data explain the difference with the intensity reported in GTF 2015.

23. The country exceeded the target according to Chinese statistics, achiev-ing an 18.4% reduction in energy intensity in 2011–15. See the Chinese government’s “Notice of the State Council on Printing and Distributing the Comprehensive Energy-Saving and Emission-Reduction Work Plan in the 13th Five-Year Plan,” published January 2017, at http://www.gov.cn /zhengce/content/2017–01/05/content_5156789.htm.

24. See the EESL website at http://www.eeslindia.org/User_Panel/UserView .aspx?TypeID=1145.

25. Ibid.

REFERENCES

IEA (International Energy Agency). 2010. Power Generation from Coal: Mea-suring and Reporting Efficiency Performance and CO2 Emissions. Paris: OECD/

IEA.

———. 2013. Energy Efficiency Market Report 2013. Paris: OECD/IEA.

———. 2014a. Energy Efficiency Market Report 2014. Paris: OECD/IEA.

———. 2014b. World Energy Outlook 2014. Paris: OECD/IEA.

———. 2014c. Energy Efficiency Indicators: Fundamentals on Statistics. Paris:

OECD/IEA.

———. 2015a. Energy Efficiency Market Report 2015. Paris: OECD/IEA.

———. 2015b. World Energy Outlook 2015. Paris: OECD/IEA.

———. 2015c. Achievements of Appliance Energy Efficiency Standards and Label-ling Programs: A Global Assessment. Paris: OECD/IEA

———. 2016a. Energy Efficiency Market Report 2016. Paris: OECD/IEA.

———. 2016b. World Energy Outlook 2016. Paris: OECD/IEA.

———. 2016c. Energy Efficiency Indicators – Highlights. Paris: OECD/IEA.

PTI. 2016. “Retail Price of LED Bulbs under Govt’s UJALA Scheme Drops to Rs 65 from Rs 550.” Indian Express. November 28.

Singh, S. C. 2016. “Prices of LED Bulbs Drop to Rs 38.” India Times. September 15.

World Bank and International Energy Agency. 2013. Sustainable Energy for All 2013–2014: Global Tracking Framework. Washington, DC: World Bank/IEA.

———. 2015. Progress toward Sustainable Energy 2015: Global Tracking Framework Report. Washington, DC: World Bank/IEA.

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