Transcript Introduction to Energy Efficiency Indicators

International Workshop on Energy Statistics
Mexico, 2-5 December 2008
Do “traditional” supply-demand data give a sufficient basis
for sound energy efficiency policies?
Introduction to Energy Efficiency Indicators
Jean-Yves Garnier
Energy Statistics Division
© OECD/IEA – 2008
International Energy Agency
Why is it important to have detailed energy
efficiency indicators?
To support any sound energy policy
 A need to know what are the sub-sectors which consume
“too much” energy (ex: trucks, heating, cement, offices, ..)
 What is ‘too much”? A need to have benchmarking and
best practices
 A need to compare with the situation in “similar” countries
(climate, size, economy, …)
To monitor progresses (or failures) of actions
and programs on energy efficiency
To be used as the basis for detailed modeling
and forecasts
© OECD/IEA – 2008
Contribution to Energy Savings
from Sectors and End Uses
IEA-11
Other
Manufacturing
14%
Space Heating 19%
Appliances 3%
Other
Household 1%
Primary
Metals 13%
Car Travel 8%
Nonmetallic
Minerals 4%
Air Travel 6%
Chemicals 9%
Truck Freight 1%
Other Freight 2%
Paper & Pulp 2%
Service 18%
Indicators are useful to understand the past…
© OECD/IEA – 2008
… as well as the future
Electricity consumption (TWh)
1000
900
800
Other
Circulation pumps
PCs
Standby
700
Television
600
Dishwashing
500
Clothes-drying
400
Clothes-washing
Refrigeration
300
Lighting
200
Cooking
100
Water heating
0
1990 1995 2000 2005 2010 2015 2020 2025 2030
© OECD/IEA – 2008
Space cooling
Space heating
The more detailed information you collect
the better you know what really happens
160%
150%
140%
Total Energy
1973 = 100%
130%
Basic energy
statistics
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
150%
Total Energy, CC
140%
1973 = 100%
130%
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
Total Energy, CC
150%
Total/Capita
140%
1973 = 100%
130%
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
Total Energy, CC
150%
Total/Capita
Total/household
140%
1973 = 100%
130%
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
Total Energy, CC
150%
Total/Capita
Total/household
140%
Total/Sq. m
1973 = 100%
130%
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
Total Energy, CC
Total/Capita
Total/household
Total/Sq. m
Space heat/Sq. m
150%
140%
1973 = 100%
130%
120%
110%
100%
90%
80%
© OECD/IEA – 2008
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73
70%
The more detailed information you collect
the better you know what really happens
160%
Total Energy
Total Energy, CC
Total/Capita
Total/household
Total/Sq. m
Space heat/Sq. m
Useful space heat/sq. m
150%
140%
1973 = 100%
130%
120%
110%
100%
90%
Detailed indicators
80%
© OECD/IEA – 2008
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82
19
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80
19
79
19
78
19
77
19
76
19
75
19
74
19
19
73
70%
The more detailed information you collect
the better you know what really happens
160%
150%
Total Energy
Space heat/Sq. m
140%
1973 = 100%
Macro
130%
120%
110%
100%
90%
80%
70%
© OECD/IEA – 2008
Macro and micro data can
lead to diverging
conclusions
Micro
Energy Balance
People's Republic of China / République populaire de Chine : 2005
Thousand tonnes of oil equivalent / Milliers de tonnes d'équivalent pétrole
SUPPLY AND
CONSUMPTION
Coal
Nuclear
Chaleur
Total
Production
Imports
Exports
Intl. Marine Bunkers
Stock Changes
TPES
1145355
14893
-55279
-17345
1087624
181427
126817
-8067
788
300965
41493
-16722
-7642
288
17417
42621
-2484
40137
13835
13835
34143
34143
-
223561
223561
431
-963
-532
-
Transfers
Statistical Differences
Electricity Plants
CHP Plants
Heat Plants
Gas Works
Petroleum Refineries
Coal Transformation
Liquefaction Plants
Other Transformation
Own Use
Distribution Losses
TFC
7118
-527596
-71089
-6640
-69485
-46624
373308
-74
-1328
-213
-3
-290405
-5037
3905
88
917
-15059
-2672
-144
283439
-17434
-20
266532
-1137
-2637
-1938
4841
-6549
-864
31852
-13835
-
-34143
-
-
-861
-503
222197
214780
-28398
-14494
171355
54660
-10647
-630
43383
279763
102809
28095
8147
85282
3226
9117
3628
11818
8551
1870
3200
9378
4642
2509
2509
35753
3011
5380
1559
8904
1067
3834
1225
1577
761
268
4161
1572
2434
12366
894
5589
791
2540
459
1360
151
218
65
14
125
64
98
-
-
-
-
116217
21882
21588
12639
12179
2580
13801
4337
4123
4019
1114
2012
8288
7656
29153
3667
12899
1811
149
625
978
303
1977
2373
127
111
3685
448
1737
1737
-
-
114230
2095
7566
75740
14944
4636
9248
1
430593
331502
41576
40885
16630
No breakdown by end
use and by function of
buildings (hospitals,
schools, hotels, offices,
108334
79
2095
- etc.)
restaurants,
7566
-
4080
4079
1
1
-
75670
9129
4627
9247
-
70
9
-
-
-
-
-
61076
17598
22302
21175
-
12071
8895
3177
-
-
-
-
222197
222197
-
53401
24293
10040
7536
11532
14230
12356
867
18
988
61369
33590
-
7336
7336
7336
-
-
-
-
-
-
60634
60634
94145
94145
11931
11931
90203
90203
397017
397017
-
-
2504
2504
12645
12645
-
OTHER SECTORS
Residential
Comm. and Publ. Services
Agriculture/Forestry
Fishing
Non-specified
238
61076
46162
NON-ENERGY USE
67380
46162
5190
12155
3872
17598
22085
238
238
in Industry/Transf./Energy
of which: Feedstocks
in Transport
in Other Sectors
22085
-
1158
1158
1158
-
1972267
2091954
2091954
-
5190
-
22302
12155
- 21175
Electr. Generated - GWh
1972267
Electricity Plants
CHP Plants
Heat Generated - TJ
CHP Plants
Heat Plants
-
-
3872
238
Comb. Electricité
ren. &
déchets
Total
Produits
pétroliers
67380
Hydro Géotherm.
solaire
etc.
Heat
Pétrole
brut
TRANSPORT SECTOR
International Aviation
Domestic Aviation
Road
Rail
Pipeline Transport
Domestic Navigation
Non-specified
Gaz Nucléaire
Hydro Geotherm. Combust. Electricity
Solar
Renew.
etc.
& Waste
Charbon
Paper Pulp and Printing
Wood and Wood Products
Construction
Textile and Leather
Non-specified
© OECD/IEA – 2008
Gas
APPROVISIONNEMENT
ET DEMANDE
No breakdown by end
use:
- heating
- DHW
- lighting
INDUSTRY SECTOR
Iron and Steel
Chemical and Petrochemical
- cooking
Non-Ferrous Metals
Minerals
Transport Equipment
- air conditioning Non-Metallic
Machinery
Mining and Quarrying
- appliances
Food and Tobacco
OTHER SECTORS
Residential
Comm. & Pub. Services
Agriculture/Forestry
Fishing
Non-specified
Crude Petroleum
Oil Products
-
12071
8895
61369
3177
-
-
-
-53088
53088
-
-
-
--
-
222197
222197
-
What most
organisations
collects on a
regular basis
is limited to
aggregated
levels
1640944
183634
-83514
-7642
-16269
1717153
13
5570
-379565
-21545
-1943
-6966
-69485
-114690
-16009
1112532
475761
132263
73550
24947
109054
7956
29091
9644
19714
15768
3392
9608
22987
17788
53401 14230 188090
24293
12356 156840
91948
91948
42084
10040
-
-
867
11931
18
14286
-
-
-
11532
988
5033
-
7536
2497441
2497441
2288947
2288947
Only a minimum set of indicators can be derived
from basic statistics
OECD
© OECD/IEA – 2008
China
India
World
Only a minimum set of indicators can be derived
from basic statistics
OECD
China
India
World
Production
Mtoe
3 834
1 641
419
11 468
TPES
Mtoe
5 548
1 717
537
11 434
Electricity Consumption
TWh
9 800
2 322
525
16 695
Mt of CO2
12 910
5 059
1 147
27 136
CO2 Emissions
© OECD/IEA – 2008
Only a minimum set of indicators can be derived
from basic statistics
OECD
China
India
World
Production
Mtoe
3 834
1 641
419
11 468
TPES
Mtoe
5 548
1 717
537
11 434
Electricity Consumption
TWh
9 800
2 322
525
16 695
Mt of CO2
12 910
5 059
1 147
27 136
0.69
0.96
0.78
1.00
toe / 000 2000$
0.20
0.91
0.83
0.32
TPES/GDP(PPP)
toe / 000 2000$ PPP
0.18
0.22
0.16
0.21
TPES/Population
toe / capita
4.74
1.32
0.49
1.78
CO2 Emissions
Production/TPES
TPES/GDP
© OECD/IEA – 2008
Only a minimum set of indicators can be derived
from basic statistics
OECD
China
India
World
Production
Mtoe
3 834
1 641
419
11 468
TPES
Mtoe
5 548
1 717
537
11 434
Electricity Consumption
TWh
9 800
2 322
525
16 695
Mt of CO2
12 910
5 059
1 147
27 136
0.69
0.96
0.78
1.00
toe / 000 2000$
0.20
0.91
0.83
0.32
TPES/GDP(PPP)
toe / 000 2000$ PPP
0.18
0.22
0.16
0.21
TPES/Population
toe / capita
4.74
1.32
0.49
1.78
kWh / capita
8 365
1 781
480
2 596
CO2 Emissions
Production/TPES
TPES/GDP
Elec. Cons/Population
© OECD/IEA – 2008
Only a minimum set of indicators can be derived
from basic statistics
OECD
China
India
World
Production
Mtoe
3 834
1 641
419
11 468
TPES
Mtoe
5 548
1 717
537
11 434
Electricity Consumption
TWh
9 800
2 322
525
16 695
Mt of CO2
12 910
5 059
1 147
27 136
0.69
0.96
0.78
1.00
toe / 000 2000$
0.20
0.91
0.83
0.32
TPES/GDP(PPP)
toe / 000 2000$ PPP
0.18
0.22
0.16
0.21
TPES/Population
toe / capita
4.74
1.32
0.49
1.78
kWh / capita
8 365
1 781
480
2 596
CO2 / TPES
t CO2 / toe
2.33
2.95
2.14
2.37
CO2 / GDP
kg CO2 / 2000 $
0.45
2.68
1.78
0.75
CO2 / GDP (PPP)
kg CO2 / 2000 $ PPP
0.43
0.65
0.34
0.50
CO2 / Population
t CO2 / capita
11.02
3.88
1.05
4.22
CO2 Emissions
Production/TPES
TPES/GDP
Elec. Cons/Population
© OECD/IEA – 2008
Efficiency of Electricity Generation in Electricity plants
Efficiency of Electricity Generation
in Electricity Plants
Coal
33%
Australia
Efficiency of Electricity Generation
in Electricity Plants
Oil
38%
Belgium
Canada
38%
Canada
36%
Denmark
Coal
41%
France
39%
Germany
39%
35%
30%
Iceland
39%
42%
Japan
36%
Korea
38%
Italy
42%
Japan
36%
Ireland
37%
Italy
38%
Korea
Luxembourg
Luxembourg
36%
Mexico
Netherlands
34%
NZ
34%
Mexico
41%
Netherlands
30%
NZ
65%
Norway
Norway
Poland
Poland
40%
Portugal
Slovak Rep.
38%
Spain
Sweden
Switzerland
Switzerland
35%
29%
34%
Brazil
26%
India
32%
China
35%
South Africa
27%
India
35%
29%
USA
37%
Brazil
41%
UK
36%
USA
South Africa
35%
Turkey
38%
UK
21%
Spain
Sweden
Turkey
39%
Portugal
30%
Slovak Rep.
34%
China
Russia
© OECD/IEA – 2008
40%
36%
Greece
Hungary
Ireland
0%
37%
France
Iceland
Oil
38%
Germany
32%
Hungary
36%
20%
Finland
35%
Greece
41%
40%
Czech Rep.
42%
Denmark
Finland
39%
Austria
Belgium
Czech Rep.
33%
Australia
42%
Austria
Russia
20%
40%
60%
2001-2005 average
80%
100%
0%
20%
40%
60%
2001-2005 average
80%
100%
The Indicator Pyramid
TPES/GDP
TPES/Production
Electricity Cons./Population
Aggregated
Indicators
CO2/GDP PPP
Efficiency Elec. Prod.
Cons./ton cement
Disaggregated
Indicators
Only a minimum
set of indicators
can be derived
from basic
statistics
© OECD/IEA – 2008
Heating Cons./sqm/DD
Litre/100km (stock)
Dry process
Process
Efficiency
Condensing boiler
Litre/100km
(vintage)
Analysts need more detailed data
180
56%
Hypothetical energy use
without efficiency improvements
160
140
EJ
120
Energy Savings
100
80
60
40
Actual energy use
20
0
1973
1980
1990
2000
2004
Contribution of energy efficiency to limited increases
in IEA energy consumption
3%
100%
28%
24%
80%
1%
60%
40%
0%
20%
-1%
Manufac-Households*Services Passenger Freight Other**
turing
transport transport
Total
16%
23%
17%
21%
23%
10%
10%
1990
2004
0%
Long-term Economy-wide Energy Savings
from Improvements in Energy Efficiency
© OECD/IEA – 2008
23%
Average annual percent change
Average annual percent change
2%
Hypothetical energy use without energy efficiency
improvements
2%
1%
0%
Energy
efficiency
improvements
Actual energy use
1973 - 1990
Energy
efficiency
improvements
Actual energy use
1990 - 2004
Impact of Energy Efficiency Improvements
on Final Energy Use, IEA11
So, what could be done to bridge the gap
(the IEA’s example)
Priority was given to cooperation
 Data on industry: network of industry association (WBCSD)
 Data on residential, services, transport: cooperation with
the ODYSSEE programme of the European Commission for
EU countries
 Cooperation with APEC for APEC Member Economies
Direct contacts with national administrations
(e.g. EIA (USDOE) for RECS, MECS, …)
In 2006, the IEA defined templates to ease the
reporting of the basic data by countries
© OECD/IEA – 2008
The initial templates
© OECD/IEA – 2008
Detailed data on transport
106
Veh-km
tonnes
Tonnes-km
pass-km
TRANSPORT
© OECD/IEA – 2008
Energy consumption broken down by end use
Services
Space Heating
Space Cooling
Lighting
Other Energy Use in Services Sector
© OECD/IEA – 2008
Diffusion, stocks and average consumption
of selected appliances
RESIDENTIAL
%
kWh/unit
106
© OECD/IEA – 2008
Payback on Investment…
Published in 2004
Published in 2007
14 IEA countries
20 IEA countries
Last year: 1998 (Y-6)
Last year: 2004 (Y-3)
Yes, but… still 10 OECD countries missing
Data are not available for all sectors in all countries
Coverage does not include major Non-OECD countries
Joint work with World Bank/LBNL to extend coverage
© OECD/IEA – 2008
Despite all the efforts
there is a risk of
widening and worrying
gap between the
interest for indicators
and the resources
allocated to collect
proper supporting data
The 3Is vs. the 3Ds
Dramatic
Decrease in
Data resources
© OECD/IEA – 2008
For
instance,
149
participants
in the
meeting on
efficiency
goals
Increasing
Interest for
Indicators
Statistics and
statisticians
are at the basis
of the pyramid
and constitute
the foundation
for any sound
analysis and
policy
So, an urgent need to fill the gap by collecting
and providing proper data to analysts
The initial templates could constitute a good common
tool to collect the data
Once again, priority was given to cooperation
 A two-day retreat with the EU-ODYSSEE people to see how
questionnaires could be harmonised
 Cooperation with APEC
 Meeting with LBNL to check consistency
 Further workshop with industry association (WBCSD)
The templates/questionnaire have been revised to take
into consideration comments and be more userfriendly
© OECD/IEA – 2008
A quick look at the new templates
List of
countries
Menu driven
© OECD/IEA – 2008
Built-in indicators
and graphs
Pre-filled time series
RESIDENTIAL
Space Heating
Space Cooling
Water Heating
Cooking
© OECD/IEA – 2008
A large choice of indicators
for sector end use
Built-in graphs of
indicators
© OECD/IEA – 2008
Why such a gap between the need to have detailed
indicators and the difficulty to build them
Lack of discussion and understanding between the parties
Lack of resources
Lack of expertise and experience
© OECD/IEA – 2008
Lack of expertise and experience
The past situation in energy statistics offices
Retirement
age
50s
40s
30s
20s
gaining experience
© OECD/IEA – 2008
passing experience
The current situation
environment
modelling
private sector
Retirement
age
50s
40s
30s
policy
20s
efficiency
© OECD/IEA – 2008




Temptation to move away from statistics is high
Young statisticians only stay a few years
Not enough time to have a full grasp of energy statistics
No time to transmit their expertise
Why such a gap between the need to have detailed
indicators and the difficulty to build them
Lack of discussion and understanding between the parties
Lack of resources
Lack of expertise and experience
On 21-22 January 2009, the IEA will organise a workshop to bring around
the same table policy makers and energy analysts in charge of energy
efficiency indicators as well as statisticians. The workshop is opened to
both OECD and selected non-OECD countries.
The objective is to highlight gaps and barriers in building and using
energy efficiency indicators and to hear from successful countries
solutions and best practices. Another objective is to discuss the role of
organisations in helping countries building the expertise and capacity to
work on indicators.
© OECD/IEA – 2008
There is an urgent need to act and react
 The Nobel Prize for Peace has been attributed to work on what the
state of the planet could be in the next decades. In March, the
OECD published another alarming report
 However, we do not even know the current situation very well
 There is a global consensus from and for Governments to urgently
take a series of measures to promote efficiency
 In order to optimise and prioritise these actions, there is first an
obvious need to have an accurate view of the energy consumption
in all sectors
 Of course, there is a cost associated to collecting and processing
the necessary data. But non optimum decisions often lead to costs
which are often much higher.
 A 1$/bl reduction in the price of oil is equivalent to “saving” of 85
M$ per day. A lot of money for collecting proper data which should
lead to reduce the tension on the oil market and therefore price of
oil.
© OECD/IEA – 2008
There is an urgent need to act and react (cont.)
 The 145US$/bl sent a clear signal to consumers to do more on energy
efficiency (even if prices have now dramatically decreased).
 Energy efficiency was at the centre of the discussion of the last IEA
Ministerial meeting; it will also be one of the focuses of the
discussions at the next G8 and G20 Summits in Hokkaido-Toyako.
 There is no one single silver bullet to establish sound energy
efficiency policies. However, having a solid understanding of who
consumes what is a prerequisite for any plan of actions. So the
importance of having a detailed and timely database.
 Priorities vary from countries to countries (heating in some countries,
biomass or rural electrification in others)
 A universal template should allow all countries to chose what to
collect . The current template could be a starting point which needs to
be enriched by inputs from many other organisations.
 As for the JODI initiative, cooperation between organisations is the
main driver and their participation is essential for using the momentum
and pulling their member countries with them.
© OECD/IEA – 2008
Thank you