Transcript Faruqui-08-02-08-Historical-energy-efficiency-gains-02-08

HISTORICAL GAINS IN ENERGY
EFFICIENCY, 1949-2006
Ahmad Faruqui
Sanem Sergici
Lafayette, California
February 8, 2008
US consumption growth slowed down markedly after
the OPEC Embargo in 1973
18.0%
Growth Rate (1949-1975)
Growth Rate (1975-2006)
16.0%
Growth Rate (2007-2030)
14.0%
12.0%
8.0%
6.0%
4.0%
2.0%
Year
2
30
27
20
24
20
20
21
20
18
20
15
20
12
09
20
06
20
03
20
00
20
97
20
94
-4.0%
19
91
19
88
19
85
19
82
19
79
19
19
76
19
73
19
70
67
19
64
19
61
19
58
19
55
19
52
19
-2.0%
19
49
0.0%
19
Growth Rate (%)
10.0%
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
3
Electricity consumption in 2006 would have been
300 percent higher at pre-embargo growth rates
18000
Electricity Consumption (1950-1975)
16000
Electricity Consumption (7.5% between 1975-2006)
Electricity Consumption (2.6% between 2006-2030)
14000
Electricity Consumption (1.2% between 2006-2030)
12000
Wedge=12,571 TWh
10000
8000
6000
4000
2000
Year
Source: Data are taken from EIA Annual Energy Review 2006
4
28
25
20
22
20
19
20
16
20
13
20
10
20
20
07
04
20
01
20
98
20
95
19
92
19
89
19
86
19
83
19
80
19
77
19
74
19
19
71
68
19
65
19
62
19
59
19
56
19
53
19
19
50
0
19
Electricity Consumption (billion kWh)
Electricity Consumption (2.6% between 1975-2006)
The wedge expressed as percentage of electricity
consumption in the absence of energy savings
Wedge as % of Electricity Consumption w/o Energy Savings
90%
80%
60%
50%
40%
30%
20%
10%
Wedge as % of Consumption
Year
5
05
20
03
20
01
20
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
19
77
19
75
0%
19
Wedge as % of Consumption
70%
The wedge in logarithmic terms
ln (Electricity Consumption) (billion kWh)
10.0
9.0
8.0
7.0
ln (Electricity Consumption) (1950-1975)
6.0
ln (Electricity Consumption) (7.5% between 1975-2006)
ln (Electricity Consumption) (2.6% between 1975-2006)
ln (Electricity Consumption) (2.6% between 2006-2030)
Year
6
28
25
20
22
20
19
20
16
20
13
20
10
20
07
20
04
20
01
20
98
20
19
92
19
89
19
86
19
83
19
80
19
77
19
74
19
71
19
68
19
65
19
62
19
59
19
56
19
53
19
50
19
19
Source: Data are taken from EIA Annual Energy Review 2006
95
ln (Electricity Consumption) (1.2% between 2006-2030)
5.0
About 40 percent of total energy consumption is due
to electricity
40% of total energy consumption can be attributed to the
electric energy consumption.
Energy Consumption By Sector (2006)
Total (%)
Residential
Commercial
Industrial
Transportation
Total
Source :AEO 2008
7
Electricity+Electricity related Losses (%)
21
18
33
28
15
14
11
0
100
40
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)
8
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
9
The California Energy Commission (CEC) has quantified
the components of the wedge in the state
Residential Energy Savings (GWH)
Commercial Energy Savings (GWH)
Building & Utility and
Market
Appliance Public Agency and Price
Standards Programs
Effects Total
1990
2000
2005
2008
2013
2018
5,740
11,650
14,615
16,336
18,977
21,533
994
1,308
1,416
1,355
1,256
1,186
253
413
447
458
476
497
6,987
13,371
16,478
18,149
20,709
23,216
Source: California Energy Demand 2008-2028 Staff Report- page 28
10
Building & Utility and Market
Appliance Public Agency and Price
Standards Programs
Effects Total
2,499
6,736
9,572
11,682
15,563
19,608
398
1,358
1,987
2,132
2,094
2,052
12,109
8,259
13,724
15,420
17,135
18,447
15,006
16,353
25,283
29,234
34,792
40,108
According to CEC estimates, building& appliance standards
constitute a larger portion of energy savings for residential
customers compared to that for commercial customers
Residential Energy Savings (GWH)
Commercial Energy Savings (GWH)
Building & Utility and Market
Appliance Public Agency and Price
Standards Programs
Effects
1990
2000
2005
2008
2013
2018
82%
87%
89%
90%
92%
93%
14%
10%
9%
7%
6%
5%
4%
3%
3%
3%
2%
2%
Total
100%
100%
100%
100%
100%
100%
11
Building & Utility and Market
Appliance Public Agency and Price
Standards Programs
Effects
17%
41%
38%
40%
45%
49%
3%
8%
8%
7%
6%
5%
81%
51%
54%
53%
49%
46%
Total
100%
100%
100%
100%
100%
100%
Share of building& appliance standards in total savings
increases over time
25%
Price Effects (%)
Building& Appliance Standards (%)
Utility& Agency Programs (%)
20%
Total Energy Savings (%)
15%
10%
5%
0%
1980
1990
2000
2007
Year
12
2011
2013
2018
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
25%
Price Effects (%)
Building& Appliance Standards (%)
Utility&Agency Programs (%)
Total Savings (%)
15%
10%
5%
Year
13
20
18
20
16
20
14
20
12
20
10
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0%
19
80
Savings as % of Forecasted Energy
20%
Additional evidence comes from a paper entitled,
“Energy Efficiency Policies: A Retrospective
Examination” (*)
This paper reviews the literature and identifies up to 4 quads
annual 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.
14
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 preembargo 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
15
450,000
45%
400,000
40%
350,000
35%
300,000
30%
250,000
25%
200,000
20%
150,000
15%
100,000
10%
Electricity Intensity
5%
50,000
Value added by Private Goods-Producing
industries as % of GDP
0%
0
19
49
19
51
19
53
19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
Electricity Intensity (thousand kWh/real GDP (Billion$))
US electricity intensity stopped growing after the 1973
embargo and began to decline in the mid-1990s
Source: BEA 2008 and Annual Energy Review 2006
Year
16
Several factors drive US electricity consumption
160
1600
Price of Electricity (2000$- cents/kWh)
Value added by Private Goods-Producing Industries as % of GDP
Value Added by Private Services-Producing Industries as % of GDP
Cooling Degree Days (CDD)
Heating Degree Days (HDD)
Electricity Consumption (billion kWh)
US GDP (2000$-billion $)
1200
100
1000
80
800
60
600
40
400
20
200
Year
Source: Data are taken from EIA AER 2006 and BEA 2008
17
05
03
20
01
20
99
20
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
19
77
19
75
19
73
19
71
19
69
19
67
19
65
19
63
19
61
19
59
19
57
19
55
19
53
19
19
19
51
0
49
0
Index value (1949=100)
1400
120
19
Index Value (1949=100)-- for price of electricity 1960=100
140
U.S. Cooling and Heating Degree Days- 1949-2006
Price of Electricity- 1960-2006
140
100
80
60
40
20
Cooling Degree Days (CDD)
Heating Degree Days (HDD)
Price of Electricity (2000$- cents/kWh)
0
19
49
19
51
19
53
19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
Index Value (1949=100)-- for price of electricity 1960=100
120
Year
Source: Annual Energy Review 2006
18
Value Added Shares of Goods and Services Industries
as % of U.S. GDP- 1949-2006
160
140
100
80
60
40
Value added by Private Goods-Producing Industries as % of GDP
20
Value Added by Private Services-Producing Industries as % of GDP
0
19
49
19
51
19
53
19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
Index Value (1949=100)
120
Source: BEA
Year
19
U.S. GDP and Electricity Consumption- 1949-2006
U.S. GDP and Electricity Consumption- 1949-2006
1600
1400
1000
800
600
400
200
Electricity Consumption (billion kWh)
US GDP (2000$-billion $)
0
19
49
19
51
19
53
19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
Index Value (1949=100)
1200
Source: Annual Energy Review 2006
Year
20
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
21
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
22
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.
23
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
Std Dev
Min
Max
Mean
Median
Mode
0.04
0.3%
20%
3%
2%
1%
2020
0.08
1.0%
45%
6%
3%
2%
2030
0.10
1.0%
50%
8%
5%
5%
Mean values for 2010, 2020, and 2030 are respectively 3%, 6%,
and 8%
24
Distribution of Responses: Q1, 2010
Distribution of Responses for 2010
30
2010
25
Frequency
20
15
10
5
0
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%
Response
25
NA
Distribution of Responses: Q1, 2020
Distribution of Responses for 2020
16
2020
14
12
Frequency
10
8
6
4
2
0
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%
Response
26
NA
Distribution of Responses: Q1, 2030
Distribution of Responses for 2030
16
2030
14
12
Frequency
10
8
6
4
2
0
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%
Response
27
NA
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)?
% of Load Growth Offset by EE
Std Dev
Min
Max
Mean
Median
Mode
0.22
10%
100%
40%
25%
25%
On the average, participants conjecture that 40% of the
projected increase will be offset by EE.
28
Distribution of Responses: Q2
Distribution of Responses
16
Frequency
14
12
Frequency
10
8
6
4
2
0
0-10%
10-20%
20-30%
30-40%
40-50%
50-60%
Response
29
60-70%
70-80%
80-90%
90-100%
NA