HISTORICAL GAINS IN ENERGY EFFICIENCY, 1949-2006

Ahmad FaruquiSanem Sergici

Lafayette, California

February 8, 2008

2

US consumption growth slowed down markedly after the OPEC Embargo in 1973

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

Year

Gro

wth

Rat

e (%

)

Growth Rate (1949-1975)

Growth Rate (1975-2006)

Growth Rate (2007-2030)

3

The slow down in growth can be used to derive an upper-bound for the gain in energy efficiency

• By fitting a simply regression model, we have estimated the annual (exponential) growth rate of electricity consumption during 1949-1972 period at 7.6%

► This is what the growth rate would have been during the post-75 period absent the EE initiatives and other factors (such as structural change in the economy and slower growth in productivity)

• Using the same methodology, we have estimated the growth rate of electricity consumption during 1975-2006 period at 2.5%

• The wedge between electricity consumption series w/ and w/o energy efficiency gains is 12,571 TWh in 2006

4

Electricity consumption in 2006 would have been 300 percent higher at pre-embargo growth rates

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14000

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18000

Year

Ele

ctri

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Con

sum

pti

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(b

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kW

h)

Electricity Consumption (1950-1975)

Electricity Consumption (7.5% between 1975-2006)

Electricity Consumption (2.6% between 1975-2006)

Electricity Consumption (2.6% between 2006-2030)

Electricity Consumption (1.2% between 2006-2030)

Source: Data are taken from EIA Annual Energy Review 2006

Wedge=12,571 TWh

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The wedge expressed as percentage of electricity consumption in the absence of energy savings

Wedge as % of Electricity Consumption w/o Energy Savings

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Wedge as % of Consumption

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The wedge in logarithmic terms

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Year

ln (

Ele

ctri

city

Con

sum

ptio

n) (

billi

on k

Wh)

ln (Electricity Consumption) (1950-1975)

ln (Electricity Consumption) (7.5% between 1975-2006)

ln (Electricity Consumption) (2.6% between 1975-2006)

ln (Electricity Consumption) (2.6% between 2006-2030)

ln (Electricity Consumption) (1.2% between 2006-2030)

Source: Data are taken from EIA Annual Energy Review 2006

7

About 40 percent of total energy consumption is due to electricity

Energy Consumption By Sector (2006) Total (%) Electricity+Electricity related Losses (%)

Residential 21 15Commercial 18 14Industrial 33 11Transportation 28 0

Total 100 40

Source :AEO 2008

40% of total energy consumption can be attributed to the electric energy consumption.

8

ACEEE has also quantified the historical gain in energy efficiency for the US as a whole

Between 1970-2006, total U.S. energy consumption increased from 68 to 100 quads

• ACEEE finds that absent the efficiencies, U.S. energy consumption would have been 200 quads in 2006

• This corresponds to a wedge of 100 quads (29,310 TWh)

• 11,724 TWh (or 40 percent) of this wedge can be attributed to electricity savings

• This is very close to our estimate of the wedge (12,571 TWh)

9

Question of the day

• What are the components of the wedge?

• I.e., what is the role of the following factors:► Electricity prices► Codes and standards for appliances and buildings► Lower GNP growth► Structural change in the economy away from heavy

industry► Utility DSM programs

• The answers to these questions are available in bits and pieces

10

The California Energy Commission (CEC) has quantified the components of the wedge in the state

Building & Appliance Standards

Utility and Public Agency Programs

Market and Price Effects Total

Building & Appliance Standards

Utility and Public Agency Programs

Market and Price Effects Total

1990 5,740 994 253 6,987 2,499 398 12,109 15,0062000 11,650 1,308 413 13,371 6,736 1,358 8,259 16,3532005 14,615 1,416 447 16,478 9,572 1,987 13,724 25,2832008 16,336 1,355 458 18,149 11,682 2,132 15,420 29,2342013 18,977 1,256 476 20,709 15,563 2,094 17,135 34,7922018 21,533 1,186 497 23,216 19,608 2,052 18,447 40,108

Commercial Energy Savings (GWH) Residential Energy Savings (GWH)

Source: California Energy Demand 2008-2028 Staff Report- page 28

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According to CEC estimates, building& appliance standards constitute a larger portion of energy savings for residential customers compared to that for commercial customers

Building & Appliance Standards

Utility and Public Agency

Programs

Market and Price

Effects Total

Building & Appliance Standards

Utility and Public Agency

Programs

Market and Price

Effects Total

1990 82% 14% 4% 100% 17% 3% 81% 100%2000 87% 10% 3% 100% 41% 8% 51% 100%2005 89% 9% 3% 100% 38% 8% 54% 100%2008 90% 7% 3% 100% 40% 7% 53% 100%2013 92% 6% 2% 100% 45% 6% 49% 100%2018 93% 5% 2% 100% 49% 5% 46% 100%

Residential Energy Savings (GWH) Commercial Energy Savings (GWH)

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Share of building& appliance standards in total savings increases over time

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5%

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20%

25%

1980 1990 2000 2007 2011 2013 2018Year

Price Effects (%)

Building& Appliance Standards (%)

Utility& Agency Programs (%)

Total Energy Savings (%)

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Savings due to utility and agency programs expressed as percentages of total load forecast remain relatively constant over time

Percentage of Load Forecast Offset by DSM Activities

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Sav

ings

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orec

aste

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Price Effects (%)Building& Appliance Standards (%)Utility&Agency Programs (%)Total Savings (%)

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Additional evidence comes from a paper entitled, “Energy Efficiency Policies: A Retrospective Examination” (*)

This paper reviews the literature and identifies up to 4 quadsannual energy savings (approximately 1,172 TWh)

• At least half is attributable to appliance standards and utility based DSM

• Implementation of residential appliance standards leads to an estimated residential annual electricity energy savings of 0.59 quads (approximately 172 TWh) in 2000

• Incremental energy savings from our analysis is 713 TWh in 2000► 24% (172/713) of the savings can be attributed to the residential

appliance standards

Total electric energy consumed in 2000 was 3,592 TWh (EIA, AER 2006)

• This implies that residential appliance standards saved 5%(172/3592) of total electric energy consumed in 2000

(*) Gillingham, Kenneth, R. Newell, and K. Palmer (2006), “Energy Efficiency Policies: A Retrospective Examination,”Annual Review of Environmental Resources, 31:161-92.

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EIA has compiled data on utility DSM spending levels and associated efficiency gains

This implies that utility based DSM programs saved 1.5% total electric energy consumed in 2000 (but the reference point is not pre-embargo trends).

54 TWh in 2000 corresponds to 8% (54/659) of the total savings we have estimated for 2000.

Source: Energy Efficiency Policies: A Retrospective Examination, 2006

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US electricity intensity stopped growing after the 1973 embargo and began to decline in the mid-1990s

0

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100,000

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250,000

300,000

350,000

400,000

450,000

Year

Ele

ctri

city

In

ten

sity

(th

ou

san

d k

Wh

/rea

l G

DP

(B

illi

on

$))

0%

5%

10%

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25%

30%

35%

40%

45%

Electricity Intensity

Value added by Private Goods-Producingindustries as % of GDP

Source: BEA 2008 and Annual Energy Review 2006

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Several factors drive US electricity consumption

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60

=1

00

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Ind

ex v

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Price of Electricity (2000$- cents/kWh)Value added by Private Goods-Producing Industries as % of GDPValue Added by Private Services-Producing Industries as % of GDPCooling Degree Days (CDD)Heating Degree Days (HDD)Electricity Consumption (billion kWh)US GDP (2000$-billion $)

Source: Data are taken from EIA AER 2006 and BEA 2008

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U.S. Cooling and Heating Degree Days- 1949-2006Price of Electricity- 1960-2006

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Cooling Degree Days (CDD)

Heating Degree Days (HDD)

Price of Electricity (2000$- cents/kWh)

Source: Annual Energy Review 2006

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Value Added Shares of Goods and Services Industries as % of U.S. GDP- 1949-2006

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ex V

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Value added by Private Goods-Producing Industries as % of GDP

Value Added by Private Services-Producing Industries as % of GDP

Source: BEA

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U.S. GDP and Electricity Consumption- 1949-2006

U.S. GDP and Electricity Consumption- 1949-2006

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Electricity Consumption (billion kWh)

US GDP (2000$-billion $)

Source: Annual Energy Review 2006

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So how we do put all this together?

• Regression models are being run with different combinations of variables to decompose the wedge

• Initial results are encouraging► Price effect has been estimated► GNP effect has been estimated► Weather effects are minimal► The rest can be attributed to efficiency programs and

codes and standards

• Results will be available sometime next week

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What is the future potential for energy efficiency?

• A detailed end-use cum regional assessment is being carried out by Global

• Aggregate results at the national level are now available from an expert survey

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Survey results : Part I

Part I involved 2 questions.• 50 survey participants returned their Part I

responses.• Not all 50 participants opined on all questions in

Part I- there are several blank responses for each question.

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Q1- In your view, at the national level, what percent of annual industry revenues are likely to be spent on energy efficiency in each year below?

2010 2020 2030

Std Dev 0.04 0.08 0.10Min 0.3% 1.0% 1.0%Max 20% 45% 50%Mean 3% 6% 8%Median 2% 3% 5%Mode 1% 2% 5%

Mean values for 2010, 2020, and 2030 are respectively 3%, 6%, and 8%

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Distribution of Responses: Q1, 2010

Distribution of Responses for 2010

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0-2% 2-4% 4-6% 6-8% 8-10% 10-12% 12-14% 14-16% 16-18% 18-20% 20-22% 22-24% 24-26% 26-28% 28-30% NA

Response

Fre

qu

ency

2010

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Distribution of Responses: Q1, 2020

Distribution of Responses for 2020

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0-2% 2-4% 4-6% 6-8% 8-10% 10-12% 12-14% 14-16% 16-18% 18-20% 20-22% 22-24% 24-26% 26-28% 28-30% NA

Response

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2020

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Distribution of Responses: Q1, 2030

Distribution of Responses for 2030

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Response

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2030

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Q2- In the preliminary 2008 Annual Energy Outlook “Reference” Forecast from the U.S. Energy Information Administration, U.S. electricity consumption is projected to increase by 30% between 2008 and 2030. In your view, how much of this projected load

growth is likely to be offset by energy efficiency (EE)?

On the average, participants conjecture that 40% of the projected increase will be offset by EE.

Std Dev 0.22Min 10%Max 100%Mean 40%Median 25%Mode 25%

% of Load Growth Offset by EE

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Distribution of Responses: Q2

Distribution of Responses

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16

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90-100% NA

Response

Fre

qu

ency

Frequency