Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del...

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Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica

Transcript of Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del...

Page 1: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Advanced indicators

Bruno Lapillonne, Vice President, Enerdata

Reunión Técnica de Trabajo del Proyecto BIEE24 – 26 de febrero, 2014, San José, Costa Rica

Page 2: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Out

line

1. Energy efficiency index2. Energy savings 3. Decomposition of power sector consumption

Page 3: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

How energy efficiency progress is measured in ODYSSEE?

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• Progress in energy efficiency for final consumers is measured in ODYSSEE through an indicator, called ODEX, that is as much as possible cleaned from structural changes or other factors that have nothing to do with energy efficiency (e.g. increase in comfort or in equipment ownership, structural changes in industry, climate variations from one year to the other)

• For each end-use sector (industry, transport, households, services), energy efficiency progress is measured at a detailed level by sub-sector (or end-use, or mode of transport), through reduction in specific energy consumption measured in physical units, to get an energy efficiency index by sector.

• Energy efficiency progress is then evaluated at the level of the whole economy by weighting energy efficiency progress of each end-use sector, on the basis of their share in the final energy consumption.

ODEX (“ODYSSEE energy efficiency index”)

Page 4: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

How ODEX is calculated for each sector?

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• ODEX by sector is calculated from unit consumption trends by sub –sector (or end-use or mode of transport )o By aggregation of unit consumption indices by sub-sector in one

index for the sector on the basis of the current weight of each sub-sector in the sector’s energy consumption;

o Unit consumption by sub-sector are expressed in different physical units so as to be as close as possible to energy efficiency evaluation : toe/ m2, toe/employee, kWh/appliance, toe/ton, litre/100km,…

• ODEX is calculated on the basis of up to 35 sub- sectors (up to 7 modes in transport, 9 end-uses for households, 14 branches in industry and 5 sub-sectors in services.

Page 5: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency index (ODEX) for final consumers (EU-27)

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2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 201080

82

84

86

88

90

92

94

96

98

100

Industry Transport Households (technical) Total

100=

2000

ODEX= 88 in 2010 12% energy efficiency improvement between 2000 and 2010 .

Regular and larger gains for households (1.6%/year).

No progress for industry since the beginning of the economic crisis (1.2%/year until 2007)

Lower progress for transport (0.9%/year), due to negative savings for the transport of goods since the economic crisis.

ODEX calculated as a 3 years moving average to avoid short term fluctuations (imperfect climatic corrections, behavioural factors, business cycles). Services not included due to the difficulty of measuring energy savings .

ODEX indicators: case of EU averaage

ESD

Page 6: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency improvement for final consumers in EU countries

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• Energy efficiency improvement from ODEX can also be expressed in %/year to assess the average annual rate of energy efficiency improvements;

• 12% energy efficiency improvement between 2000 and 2010 at EU level means an average rate of improvement of 1.2%/year;

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tvia

Rom

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Slov

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Nor

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Net

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Fran

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Ger

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Hun

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and EU

Den

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Swed

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0.0

0.5

1.0

1.5

2.0

2.5

3.0

2000-2010

%/y

ear

Rate of annual energy efficiency progress based on ODEX

Page 7: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency index for industry

Evaluation carried out at the level of up to 14 branches, of which 3 energy intensive branches: steel, cement and pulp & paper. For each branch energy efficiency improvement is measured from the decrease of the specific energy consumption expressed in terms of energy used

per ton produced for energy intensive products (steel, cement, glass and paper)

per unit of production index for the other branches

Page 8: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Around 25% progress in energy efficiency in industry in the EU-27 since 1990; slow progression since 1998 (1,4 %/year compared to 2.2%/year from 1990 to 1998)

Not all branches are shown for sake of clarity

Trends in ODEX in industry (EU-27)

Page 9: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency index: principle of calculation: 1 Calculation of indices by branch and weighting

Energy ratios1990 1991 1992 1995

Chemicals (toe/100)(index)

8.5(100)

8.3(98)

8.2(96)

8.2(96)

Steel (toe/tonne) (index)

0.30(100)

0.29(97)

0.26(87)

0.25(83)

Energy consumption (weight)

Chemicals (Mtoe) (%)

20(50)

20(48)

20(44)

22(46)

Steel (Mtoe) (%)

20(50)

22(52)

25(56)

26(54)

Page 10: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency index: principle of calculation:

2 Calculation of sector index (year t-1 as reference)

Energy efficiency index

1990 1991 1992 1993

Chemicals 100 98 96 96

Steel 100 97 87 83

Total 100 97,4 90,9 88,6

IE91 = IE1990 x (98 x 0.48 + 97 x 0.52) = 97,4

IE92 = IE1991 x (96/98 x 0.44 + 87/97 x 0.56) = 90.9

IE93 = IE1990 x (96/96 x 0.46 + 83/87 x 0.54) = 88,6

gains of 11.4% in 1993 compared to 1990

Page 11: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency index for households

Calculated on 8 end-uses/appliances : heating, water heating, cooking, 5 large appliances (refrigerators, freezers, washing machine , dishwashers and TV)Indicators used:Heating: unit consumption per m2 at normal climate (toe/m2) (per dwelling equivalent with central heating)Water heating: unit consumption per dwelling with water heatingCooking: unit consumption per dwellingLarge elec. appliances: specific consumption per appliance (kWh/year)

Page 12: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Energy efficiency progress for households in the EU-27

ODEX is an index weighting the energy efficiency progress for 8 end-uses/appliances.

Energy efficiency improved by 20% over the period 2000-2012, ie by 1.9%/year;Since 1990 the improvement reaches 31% (or about 1.6%/year). The efficiency improvement for heating reaches 20% since 2000 and 14% for large electrical appliances

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1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

65

70

75

80

85

90

95

100

Large elec appliances Heating

Efficiency index Water heating

Cooking

Page 13: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Out

line

1. ODEX 2. Energy savings 3. Decomposition of of power sector consumption

Page 14: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

How to measure energy savings

Two methods that are equivalent can be used to calculate energy savings by sector (in ktoe or GWh):

Sum the energy savings for each sub-sector (or end-use);

Direct calculation at sector level with ODEX indicator

Page 15: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

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Calculation of energy savings by end-use or sub-sector : example of refrigerators

The savings are given by the reduction in the specific consumption, in kWh/year for refrigerators or liters/100 km for cars. A reduction of the average specific consumption of the refrigerator 'stock from 400 to 300 kWh per year in a country with 2 million of refrigerators will result in total electricity savings equal to 100 GWh in 2007 compared to 1990.

•Energy savings in 2007 (compared to 1990) = 100 GWh ((400-300)*1 )

assuming a stock of 1 M refrigerators in 2007

•Rate of energy savings: 25% (=100/400)

Page 16: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Calculation of energy savings by sub-sector: case of cement industry

Definition : at the level of an industrial branch i, energy savings are calculated from the variation of the consumption Ei due to a reduction in the specific energy consumption Ei/Qi between year t and a base year, as :

Qt*(Eit/Qit-Eio/Qio) (Qi= output)

Example: case of energy savings in cement production between 1990 and 2010– 1990 : Consumption : 0.85 Mtoe; production 10 Mt and specific energy

consumption 0,085 toe/tonne

– 2010: Consumption : 1.2 Mtoe; production 15 Mt and 0,08 toe/tonne

Energy savings 15* (0,085- 0,08)=- 0.075 Mtoe

Page 17: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Calculation of energy sector directly at sector level with ODEX

• Energy Savings (ES) can be directly derived from ODEX • ODEX is equal to the ratio between the energy consumption at year t (E) and

a fictive consumption that would have happened without energy savings (ES): ODEX=E/(E+ES)*100 ES = E x ((100/ODEX)-1)

• If energy consumption = 50 Mtoe and ODEX =80 Energy savings =50* ((100/80)-1)=12.5 Mtoe

Page 18: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Mtoe

Energy savings fro households (EU-27)

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

0

2

4

6

8

10

0102030405060708090100110120130140

Annual savingsCumulative savings since 2000

Annu

al e

nerg

y sa

ving

s(M

toe/

year

)

Cum

ultiv

e en

ergy

savi

ngs (

Mto

e)

Energy savings for households exceeded 70 Mtoe since 2000 : without energy efficiency improvement, the energy consumption would have been 70 Mtoe higher in 2012, ie the equivalent of the total consumption for water heating,

electrical appliances and lighting;

Page 19: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Evaluation of energy savings for final consumers (EU-27)

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• About 120 Mtoe energy savings in 2010 compared to 2000 (i.e. 12% of final energy consumption). In other words without energy savings the final energy consumption would have been 12% higher in 2010.

• Around 40% of total savings in households, 31% for industry, 29% for transport

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100

20

40

60

80

100

120

Industry Transport Households

Indicators of energy savings

Page 20: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Out

line

1. ODEX 2. Energy savings 3. Decomposition of power sector consumption

Page 21: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Principles of the decomposition of the power sector

Three main effects explain the variation of the net consumption for power generation over a period*:

The increased consumption of electricity, that all things being equal, contribute to increase the losses in power generation;

Changes in the power mix between different sources with very different efficiencies o wind, hydro, PVs (100% efficiency);o Thermal (between 30 and 50% depending on fuel mix and

technology);o geothermal and nuclear (respectively 10% and 33%);

Variation in the efficiency of thermal power generation

*net consumption for power generation= sum of input and outputs for electricity generation

Page 22: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

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Decomposition of consumption for power generation: effects of increased electricity consumption

1990 20100

1

2

3

4

5

6

7

8

elec cons. cons. power sector

+ 4 Mtoe

+ 1,6 Mtoe

The increase in the electricity consumption (+1,6 Mtoe) translates into a much larger consumption in the power sector (+ 4 Mtoe);

Efficiency and power mix assumed constant and equal to 40%

Page 23: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

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Principles of the decomposition of the power sector (cont’d)

Apart from the effect of the increased consumption of electricity, the actual consumption of the power sector is in addition depending on changes in the power mix % (power mix effect) and changes in the efficiency of thermal power generation (efficiency effect).

These two effects are calculated as the difference between the actual consumption of the power sector in 2010 and a fictive consumption :

o at 1990 power mix and 2010 power efficiency for the power mix effecto At 1990 efficiency and 2010 power mix for the efficiency effect

Page 24: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

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Decomposition of consumption for power generation: effect of changes in power mix and thermal efficiency

2.03.04.05.06.07.0

+ 4 Mtoe

The increase in the electricity consumption increased consumption in the power sector by 4 Mtoe all things being equal; the actual variation in the power sector consumption is lower (3 Mtoe) due to savings from changes in power mix (0,7 Mtoe) and efficiency gains in thermal power generation (0,3 Mtoe)

-0.7 Mtoe-0.3 Mtoe

+ 3 Mtoe

Page 25: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Decomposition of the power sector consumption variationCase of Costa Rica (2005-2011)

-200

200

600

1000

ktoe

•The increasing share of thermal power generation between 2005 and 2011 in Costa Rica from 3 to 9% contributed to increase the power sector consumption, and thus the primary energy consumption by around 800 ktoe, all things being equal.•The increase of the thermal power generation efficiency from 31 to 37% resulted in marginal savings (40ktoe) due to te low share of thermal power.

Page 26: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Decomposition of the primary energy consumption variation (2000-2010): Case of Spain

Primary consump-tion varia-

tion

Final con-

sumption variation

Increased electricity

consumption

Efficiency of thermal plant

Power mix (renewable)

Variation of consumption

for other transforma-

tions

-10

-5

0

5

10

15Mtoe

Power sector consumption variation (-6.6 Mtoe)

In Spain, the primary consumption increased much less than the final consumption (- 4,4 Mtoe), due to significant savings in the power sector (9,3 Mtoe), of which 5,2 Mtoe due to increased efficiency of thermal power generation (penetration of CCGT) and 4.1 Mtoe due to a rapid penetration of wind and solar; these savings were partially offset by the increased consumption of electricity that contributed to raise the consumption of the power sector by 2,7 Mtoe

-4,4 Mtoe

2,2 Mtoe

Page 27: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Decomposition of the final energy consumption variation

A decomposition can be carried out for each main end-use sector (industry, transport, household and services ... As shown for electrical appliances in the household sector .

For each sector, the decomposition is calculated as the sum of the decomposition for each end-use or sub-sector, since, as we are dealing with volumes in ktoe the factors can be added

Page 28: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Decomposition of the final energy consumption variation

-140-120-100

-80-60-40-20

020406080

100120140

Variation consumption

Climate effect

Activity effect

LifestylesEnergy savings Other

Structure effect

Total industry households transport services agriculture

Mto

eConsumption increased by 16 Mtoe between 2000 and 2010Economic activity contributed to an increase of 122 Mtoe (of which 48 Mtoe due to traffic increase in transport, 42 Mtoe to more dwellings), the effect of which was more than offset by energy savings (128 Mtoe). Other drivers were: structural changes (+2 Mtoe), lifestyles (18 Mtoe), climate variation ( 32 Mtoe) and other factors (mainly behavioural changes; 26 Mtoe).

Drivers of the variation of the final energy consumption in the EU between 2000 and 2010

Page 29: Advanced indicators Bruno Lapillonne, Vice President, Enerdata Reunión Técnica de Trabajo del Proyecto BIEE 24 – 26 de febrero, 2014, San José, Costa Rica.

Decomposition of the final energy consumption variation

-180-150-120

-90-60-30

0306090

120150180

Variation consumption

Climate effectActivity effect

Other

Energy savings

Total Power industry households transport services agriculture

Mto

ePrimary energy consumption increased by 34 Mtoe between 2000 and 2010More activity (including lifestyle and penetration of electricity) contributed to an increase of 172 Mtoe;Part of the effect was offset by energy savings (162 Mtoe). Other drivers were: climate variation (32 Mtoe) and other factors (mainly behavioural changes 26 Mtoe).

Drivers of the variation of the primary energy consumption in the EU between 2000 and 2010