1 Construction and Application of Sustainable Energy Indicator in Taiwan Chien-Ming Lee, Chun-Kai Wang, Hue-Dhe Chou Institute of Natural Resource and.

1

Construction and Application of Sustainable Energy Indicator

in Taiwan

Chien-Ming Lee, Chun-Kai Wang, Hue-Dhe Chou

Institute of Natural Resource and Environmental Management / Taipei University

October,11,2004 Taipei/Taiwan

2

Content

Taiwan Energy Development Status The Meaning of Sustainable Energy D

evelopment(SED) Sustainable Indicators Construction and

Investigation in Taiwan Taiwan Indicators for Sustainabe Energ

y Development (TISED) model Conclusion

3

Taiwan Energy Development Status

9494.595

95.596

96.597

97.598

98.5%

high energy import dependence

1.00

1.50

2.00

2.50

3.00

3.50

4.00

1990 1995 2000 2005 2010 2015 2020

GDP

CO

與2

(1990

1)

指數

以年

為

BAU CO2情景CO2高能源效率情景

2020 CO2再生能源 年案GDP實質

0

20

40

60

80

100

120

1981 1986 1991 1996 2001 2003

coal oil NG LNG hydro nuclear

high fossil fuel structure

CO2 emissions coupled with GDP growth

4

Energy Development Issues

High energy import dependence, the energy supplies system is vulnerable

How to decouple CO2 emissions with economic growth

High fossil fuel share, to increase renewable energy is difficult

New energy development lacks of market competition as well as market inducements

5

Energy Development Challenges

Pursue the vision of nuclear free country Enhance the energy supplies security Promote green energy use Develop new energy technology

6

The Meaning of the SED

SED must satisfy

1. Energy Security

2. Economic Competitiveness

3. Environmental Protection

7

SED Path

Economic Competitiveness

Environmental protection

energy security

SED pathSED path

8

Sustainability Indicators Criteria(Geiz and Kutzmark,1998)

It should reflect sustainability concepts It will be defined with indicators:data in

quantitative or qualitative are available It should be based on timely information:

indicators have to relevant to the time It based on the reliable information: the data

must be dependable It reflects a strategic view: a way of choosing

actions today that will cause problems tomorrow

9

SED Investigation in Taiwan

The new idea of this research

split into energy policy sustainability(EPS) and energy development sustainability(EDS)

Choose Evaluation method

1. Balance Scorecard( BSC):used in EPS

2. DSR structure(IAEA,OECD framework): used in EDS

10

Why we need to distinguish between EPS and EDS?

EPSEPSIntermediate

IndicatorsIntermediate

Indicators EDSEDS

variables variables

Time lag

11

Balance Scorecard

Balance domestic and international energy policies

Balance short-term and long-term energy targets

Balance cause and effect : to link energy policy and energy development

balance the multi-dimensions of : energy security, economic competitiveness and environmental protection

12

Indicators of EPS

Energy Decision Integrity

Energy Supply Safety

Community ParticipationEnergy policy globalization

Energy Supply diversity and Stability

Energy Market liberalization

Energy Consumption Sustainability

Energy Technology & Education

Energy Market MechanismGreen Energy Consumption

Energy technology developmentEnergy Education

13

EPS Evaluation Structure

Implemented( )： 2 points In Planning( )： 1 point Not in planning( )： 0 points

14

Energy Decision IntegrityCommunity Participation indicators status

1. Energy decision transparency energy statistics publication Check energy target

2. Community human capital Subsidize energy community Develop energy model

3. Complementary relationship between the community and the government

Subsidize domestic NGO joint international meeting

Subsidy domestic NGO held energy policy conference

Energy policy globalization 1. Integrate international energy

development strategy

Annual participate worldwide meeting

Energy institute linkage in the worldwide

Energy policy toward market mechanism

2. Energy policy response to international treats

CO2 abatement policy Participation an internal meeting Long tern responsible project

15

Energy Supply SafetyEnergy Supply diverse indicators status

1.Pursuit nuclear free country

Nuclear free actReducing nuclear share Nuclear free launch project

2.Developing renewable energy

Renewable development actIncreasing renewable share Subsidize renewable projectRenewable portfolio system

3.Increasing green energy share

Decreasing oil and coal shareIncreasing natural gas shareGrowth of co-generation share

4.Energy emergency mechanism

Cooperation with energy producing countriesDialogue with energy producing countriespetroleum security saves energy prospects plan

16

Energy Supply Safety(cont’)

Energy Market liberalization and indicators internationalization

status

1. electricity industry management efficiency

Increase IPP shareIncrease Delivery, distribute efficiently

2. Accelerate the development of natural gas business

Reduce tariffIncrease Pipeline length

3. Enhance the petroleum market efficiency

Increase public safetyIncrease oil market mechanismIncrease gas station rate

17

Green Energy Consumption Energy Market Mechanism indicator status

1. Energy price including social cost

Reduce adverse environmental subsidy

Impose market base instrument

2. Increase energy market

competition

Increase energy productivity Increase export of energy intensive

industry

3. Sound electricity price system

Difference price between peak and load

Liberalize electricity price

Employ green energy consumption

1. Energy eco-labeling system Increase energy conservation labeling Increase energy saving products Increase government green energy

purchase

2. Household and commercial energy efficiency

Increase the numbers of ESCO Subsidy green building Subsidy energy saving vehicle Subsidy low electrical appliance

3. Monitor energy intensive industry

Increase energy audit Energy saving of energy intensive

industry

18

Energy Technology & EducationEnergy technique development indicator status

1. Encourage energy technology innovation

Subsidy R&D Growth of energy patent

2. Information and techniques spread

Energy techniques transfer Build up energy data banks Performance of cooperation with well-

known energy institute

Deeply energy education

1. Human capital accumulation

Subsidy energy papers Praise excellent institute and personal

2. School and community energy education

Subsidy elementary school energy education activity

Subsidy community energy education activity

Raise energy teachers

3. Information spread mechanism

Hold international energy conference Hold domestic energy deploy meeting

4. Public energy conservation cognition

Energy conservation conduct in media Energy website

19

EPS EvaluationEPS indicators score

Energy Decision Integrity 21.9

Community ParticipationEnergy policy Globalization

10.411.5

Energy Supply Safety 23.1

Energy supply diverse and stabilityEnergy market liberalization and internationalization

11.311.8

Energy Consumption Sustainability 15.6

Energy market mechanismGreen energy consumption

7.38.3

Energy Technology & Education 19.0

Energy technique development Deeply energy education

9.99.1

Total points 79.6

20

EPS path

75 79.6 90

Sustainability status

0 score

Sustainability path

Sustainability transit

Non-sustainable

21

Results

Total points are 79.6 (greater than 75 points), shows that the country energy policy is on the sustainability transit , however, not on the sustainability path(less than 90 points)

The energy supplies safety received the highest score with 23.1

Enhancing green energy consumption is a policy priority in the future

22

EDS Evaluation EDS dimension indicators status

Energy Security(ES)

Energy import dependence (S) Energy safety storage (D) Excess energy supply (S) Renewable share (D)

n.a

Economic Competitiveness(EC)

Energy productivity(or energy intensive) (S) Energy consumption per capita (D) Energy cost share of energy intensive

industry (D) Energy sector R&D (D) Export value per energy (S) Domestic and international energy price ratio (D)

()

n.a.

n.a

n.a

Environmental Protection(EP)

Energy intensive (D) Renewable share (D) Natural gas share (D) Pollution abatement payment of energy sector Electricity of unit fossil fuel input (D) CO2/energy (S) CO2/GDP (s) Radioactive waste (S)

n.a

23

-0.50

-0.30

-0.10

0.10

0.30

0.50

0.70

1988 1990 1992 1994 1996 1998 2000 2002 2004

ES

EC

EP

EDS

EDS Trend in Taiwan

sustainability

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Regression

Regression Equation R2

EC = 0.11 + 0.36 ES

(8.42) (4.74)

0.67

EP = -0.11 + 2.25 EC

(-1.29) (3.95)

0.59

25

Results Energy development approaches to the

sustainability path Energy security is the bases of the EDS

in Taiwan

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Establish TISED Model

Uses IAEA/IAE(2001) framework(DSR) and indicators selection

Build up a System Regression Model

27

TISED System Regression Model

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Data and Regression Equation

Observers: time series (1982 – 2003) Regression equations:14

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Regression Equation R2

Y5 = 37,709.46 + 0.093X2

(26.73)*** (20.31)***

0.95

Y6 = 8678.786 + 0.036X2

(8.09)*** (10.56)***

0.85

Y7 = 4.62 + 0.0000149X2

(44.95)*** (44.65)***

0.99

Y8= 80,615.34 + 0.99X2

(8.62)*** (32.56)***

0.98

Y9=574.7-27.1lnX5 + 9.3lnX6 + 75.5lnX7 - 36.9lnX8

(3.26)*** (-1.75)* (1.2) (3.2)*** (-3.78)***

0.56

Y14= 1.76 + 0.009X9

(11.74)*** (3.61)***

0.40

Y16 = 1.95 + 0.99lnX7 + 0.3lnX8

(3.81)*** (9.95)*** (5.33)***

0.99

30

Regression Equation R2

lnY18= 4.73 – 0.027X14 + 0.0000287X16

(73.87)*** (-4.87)*** (8.57)***

0.93

lnY24 = 18.8 + 2.84lnX14 - 6.43lnX16 + 3.331lnX22

(10.66)*** (5.51)*** (-5.15)*** (3.7)***

0.96

Y26 = 234,339 – 21,100.12X14+ 30.75X22

(4.37)*** (-3.65)*** (21.08)***

0.98

Y19 = -8.8 +1.133lnX2

(-6.5)*** (10.32)***

0.84

Y22= -732.1 + 2.5X16 – 216.394X19 + 214.4lnT

(-2.37) (37.3) ( -2.37) (-4.91)

0.99

Y43 = 23.9 +0.005X16

(11.51)*** (7.94)***

0.76

Y42 = 5.729 – 0.42lnX24 + 0.65lnX26 + 0.22lnX43

(3.16)*** (-3.37)*** (5.83)*** (1.85)*

0.87

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Calibration

energy import dependence

80

85

90

95

100

Historical data

Regression data

32

export value per unit energy

0

10

20

30

40

50

6019

8219

8319

8419

8519

8619

8719

8819

8919

9019

9119

9219

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

03

Historical data

Regression data

33

pollutants in urban area

0

20

40

60

80

100

120

Regression data

Historical data

34

CO2 Emission

0

50000

100000

150000

200000

250000

300000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Historical data Regression data

35

Simulation: GDP per capita Growth(3%,4%,5%)

36

energy intensity

9.6

9.8

10

10.2

10.4

10.6

10.8

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

3%成長預測 4%成長預測 5%成長預測

sustainab

ility

37

export value per energy

0

10

20

30

40

50

60

70

80

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 20203%成長預測 4%成長預測 5%成長預測

sustainab

ility

38

energy import dependance

95

96

97

98

99

100

101

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

3%成長預測 4%成長預測 5%成長預測

sustainab

ility

39

excess energy supply

0

2500

5000

7500

10000

12500

15000

17500

20000

22500

25000

27500

30000

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

3%成長預測 4%成長預測 5%成長預測

sustainab

ility

40

pollutants in urban area

0

10

20

30

40

50

60

70

80

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

3%成長預測 4%成長預測 5%成長預測

sustainab

ility

41

CO2 emission

050000

100000150000200000250000300000350000400000450000500000550000600000650000

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

3%成長預測 4%成長預測 5%成長預測

sustainab

ility

42

Policy Simulation: Energy Intensity Reduction (by energy intensive sector )(1%,2%,3%) ,and hold GDP per capita growth 4% as well

43

energy intensity

02468

1012

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

44

pollutants in urban area

0102030405060708090

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

45

CO2 Emission

0100000200000300000400000500000600000700000

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

46

Policy Simulation: Energy per Capita Reduction (1%,2%,3%),and hold GDP per capita growth 4% as well

47

Energy Import Dependence

889092949698

100

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

48

CO2 Emission

050000

100000150000200000250000300000350000

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

49

Export Value per Energy

05

101520253035404550

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

50

Policy Simulation: Both the Energy per Capita and Energy Intensity(by sector) Reduction (1%,2%,3%) ,and hold GDP per capita growth 4% as well

51

Energy Intensity

0

2

4

6

8

10

12

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

52

CO2 Emission

0

50000

100000

150000

200000

250000

300000

1%下降 預測 2%下降 預測 3%下降 預測

sustainab

ility

53

Conclusion

Sustainable Energy Development is the biggest priority of national sustainable development

Both energy policy and energy development are moving towards the sustainability pathway, but not on the path yet.

Enhancing green energy consumption is a policy priority in the future

54

Conclusion(Cont’)

TISED system regression model indicates that

1. Energy intensity,export value per energy,energy import dependence, excess energy supply and CO2 emissions will couple with GDP per capita growth

2. Pollutants in urban area will decouple with GDP per capita growth

55

Conclusion(Cont’)

Reduce both the energy intensity of energy intensive industry and energy per capita will improve energy intensity of economy-wide, air pollution, CO2 emissions, as well as energy import dependence, which are two of the key sustainable energy policies and measures in the future.

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Thank You for Your Attention！