cdm potential of electric power sector and energy intensive industry in china
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7/28/2019 CDM Potential of Electric Power Sector and Energy Intensive Industry in China
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Keio University/Tsingua University
3E Joint Pro ect 1999-2003
1
CDM Potential of CDM Potential of Electric Power Sector andElectric Power Sector and
EnergyEnergy--intensive industriesintensive industriesin Chinain China
Outcome of 5-Year Joint Study
of Keio University/Tsinghua University
Sponsored by NEDO (New Energy andIndustrial Technology Development
Organization) Japan
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Keio University/Tsingua University 2
Members of Joint Research Team
• Keio UniversityMitsutsune YAMAGUCHI, Professor, Faculty of Economics
Osamu KAWAGUCHI, Professor, Faculty of Science and Technology
Minoru FUJII, Senior Technical Advisor, Hitachi Engineering Co., Ltd.
Yasuhiro KONNO, Senior Technical Advisor, Hitachi Engineering Co., Ltd.
Kuniyuki NISHIMURA, Research Director, Mitsubishi Research Institute, Inc.Shuta MANO, Staff Researcher, Mitsubishi Research Institute, Inc.
• Tsinghua UniversityLu Yingyun, Professor, 3E Research Institute
Liu Deshun, Professor, Institute of Nuclear Energy Technology
Ma Yuqing, Professor, 3E Research Institute
Zhao Yong, Associate Professor, 3E Research Institute
Zhou Sheng, Lecturer, 3E Research Institute
Tong Qing, Assistant Professor, 3E Research Institute
• Members of the 3E CDM Committee in Japan
• Various staffs in Electric Power Companies in China
7/28/2019 CDM Potential of Electric Power Sector and Energy Intensive Industry in China
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Keio University/Tsingua University 3
Purpose of the study
• Contribute sustainable development of
China through promoting CDM activities
• Establish a methodology of estimating
CO2 emission reduction potential
• Provide reliable figures of emissionreduction potentials and costs of CDM inChina to prospective investors worldwide
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Characteristics of our study
• Thorough bottom-up approach
• Technology-based• Based on the actual data (especially in electricpower plant cases)
• Intense cooperation of Keio-TsinghuaUniversities as well as Academia, Industry andGovernments
• Best mix of climate and technology experts,mechanical engineers, research institute,business society of both countries
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Targeted sectors and reason
• Targeted sectors
Power GenerationIron & Steel
Paper & Pulp
Cement
Oil Refinery and Chemicals
• ReasonMajor CO2 emitters
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Process of analysis
Study and select CDM model plant and technologyStudy and select CDM model plant and technology
Estimate CO2 reduction of model plantEstimate CO2 reduction of model plant
Estimate CO2 reduction potential in ChinaEstimate CO2 reduction potential in China
Calculate CO2 reduction costsCalculate CO2 reduction costs
Estimate CO2 reduction potential in Chinacorresponding to various costEstimate CO2 reduction potential in Chinacorresponding to various cost
Calculate Baseline emissions (existing emissions)Calculate Baseline emissions (existing emissions)
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CDM potential in electric power
plants(Keio & Tsinghua U.)• Collection of basic data of all power plants in
North China (Tsinghua University and power plants in North China)
• Classification of power plantsGroup 1:50 MW units Scrap & Build Option
Group 2:100,200 MW units ModificationGroup 3:300 MW units Fuel switching
The above 3 groups account for 75% of total capacity in North China
• Selection of model units/technologies, collectionof detailed data, thereafter implementation of site survey
• Price of fuel (gas price is about 8 times higher than coal)
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Estimation of CO2 reductions
• Calculate baseline emissions
“Existing actual emissions” are used as baseline
• Estimate CO2 emission reductions of
model units by applying state-of-the-artJapanese technologies (with someexception)
• Apply model units’ reduction to all others
units
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Keio University/Tsingua University 9
Summary of CO2 emission
reduction potential (Power Plants)
73,42945,5509,0047,18011,695
Total300MWFuel switchingfrom coal to
natural gas
200MWRetrofit
100MWRetrofit
50 MWScrap &Build(50MW
to 200MW)
Unit 1000 t/y
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Keio University/Tsingua University 10
Other energy intensive industries
(Iron & steel)
Blast furnaces exceeding 1000M3, but excludes plants
already installed them
Top PressureRecovery Turbine
(TRT)
Plant capacity bigger than 1 Mtof Pig Iron, but excludes plantsalready installed them
Coke Dryquenching
(CDQ)
Targeted plantsTechnologiesJapanese state-of-the-arttechnology
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Keio University/Tsingua University 12
Comparison of CDM reduction
potential by industry
Paper industry :Reduction potential is 394∼ 1172 thousand ton-CO2. 783 thousand ton-CO2 showedabove is average.
27879
5744
783
13275
8625
45550
0 10000 20000 30000 40000 50000 60000 70000 80000
Pow er Plant
Steel Industry
Paper Industry
C em ent Industry
O il Refinery andC hem ical Industry
Reduction P otential (thousand ton-C O 2 /year)
total73429
300M W
C i f CDM d ti
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Keio University/Tsingua University 13
11695
7180
9004
45550
4764
980
783
4807
357
1892
4260
1959
6707
938
729
251
0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000
50M W Scrap & Build
100M W M odification
200M W M odification
300M W Fuel switching
C DQ
TRT
Paper Industry
Replace of sm all vertical kiln
Replace of wet-process kiln with SP
W aste heat pow er generation
Utilize of com bustible waste as fuel
Utilize of steel slag for cem ent m aterial
Residue gasification at oil refineries
Utilize of exhaust gas at ethylene plants
IG C C at chem ical fertilizer plants
Ion-exchange m em brane process at soda plants
Comparison of CDM reduction
potential by technologyReduction Potential (thousand ton-C O 2 /year)
PowerPlant
Steel Industry
C em ent
Industry
O il Refineryand
C hem ical
Industry
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Keio University/Tsingua University 14
Cost estimation methodology
( )∑= +
−−n
i
i
iii
r
MB EBSB
1 1
)(−
( )0
1 1
)( I
r
MC EC SC n
i
i
iii −+
−−∑=
(Baseline emission) (Emission after CDM project)
0
1 )1(
)( I
r
EB EC n
i
i
ii ++
−∑=
--- (Numerator means saved fuel)
∑
∑
=
=
++
−
n
i
i
n
i
i
ii
Y
I r
EB EC
1
1
0)1(
)(
(Denominator means CO2 reduction in year i)
=
SB i : revenue, EB
i : fuel cost, MB
i : maintenance cost of Baseline case
SC i : revenue, EC i : fuel cost , MC i : maintenance cost of CDM caseI 0 : initial investment cost of the project
(Carbon reduction cost per ton)
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Keio University/Tsingua University 15
Reduction potential and cost (1)
73,429Total
41.461.445,550300 MWFuel switching
12.728.39,004200 MW
Modification
8.019.47,180100 MWRetrofit
2.58.311,69550 MWScrap & Build
Cost, $/t - CO2
14 year crediting period
Cost,$/t - CO2
7 year
crediting period
ReductionPotential1,000t- CO2/y
Power Plant
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Keio University/Tsingua University 16
Reduction potential and cost (2)
5,744Total
-15.60.5980TRT
-15.31.64,764CDQ
Cost, $/t - CO2
14 year
crediting period
Cost,$/t - CO2
7 year
crediting period
ReductionPotential1,000t- CO2/y
Iron & Steel
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Keio University/Tsingua University 17
Reduction potential and cost (3)
0.9121.1394 - 1,172Replacementof main
motors etc.
Cost, $/t - CO2
14 year crediting period
Cost,$/t - CO2
7 year
crediting period
ReductionPotential1,000t- CO2/y
Paper &Pulp
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Keio University/Tsingua University 18
Reduction potential and cost (4)
-3.1-2.91,959Utilize of steel slag
for cement material
10.225.04,260Utilize of combustible waste
as fuel
-5.28.91,892Waste heat power generation
26.255.9357Replace of wet-process kiln with
Suspension Pre-heater
21.445.04,807Replace of small
vertical kiln withfluidized bed kiln
Cost,$/t - CO
2
14 year crediting period
Cost,$/t - CO2
7 year
crediting period
ReductionPotential1,000t- CO2/y
Cement
Reduction potential and cost (5)
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Keio University/Tsingua University 19
Reduction potential and cost (5)
7.524.7251Clor-alkali Replacementof diaphragm process
with ion-exchangemembrane process
-5.8-4.7729Chemical fertilizer
(Coal gasificationcombined power generation)
-33.5-19.8938Ethylene (Gas turbineinstallation and
utilization of exhaustgas for crackingfurnace)
-23.3-20.46,707Oil refinery(Gasification of oil
residue and power generation)
Cost, $/t
14 year creditingperiod
Cost, $/t
7 year creditingperiod
Reduction
Potential1,000 CO2 t/y
Oil refinery,
Chemicals
Marginal Cost Curve of
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Keio University/Tsingua University 20
Marginal Cost Curve of
CDM in China
-40-30
-20
-10
010
20
30
4050
60
70
0 20 40 60 80 100 120
C O 2 Em ission Reduction Potential (m illion ton-C O 2 /year)
R
e d u c t i o n
C
o s t
( U S
$ / t o n -
C
O
2 )
crediting period: 7years crediting period: 14years
Reduction Potential
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Keio University/Tsingua University 21
1959
6707
938
729
4764
980
11695
1892
7180
9004
45550
7834807
357
4260
251
0 5000 10000 15000 20000 25000 30000 35000 40000 45000 5000
50M W Scrap & Build100M W M odification
200M W M odification
300M W Fuel switching
C DQ
TRT
Paper IndustryReplace of sm all vertical kiln
Replace of wet-process kiln with SP
W aste heat power generation
Utilize of com bustible waste as fuel
Utilize of steel slag for cem ent m aterial
Residue gasification at oil refineries
Utilize of exhaust gas at ethylene plants
IG C C at chem ical fertilizer plants
Ion-exchange m em brane process at soda plants
$0 $4.5 $9 $18 All Potential
Reduction Potential
corresponding to credit prices
PowerPlant
Steel Industry
C em entIndustry
O il Refineryand
C hem icalIndustry
(19.4)(8.3)
(28.3)
(1.6)
(55.9)
(0.5)
(45.0)
(8.9)
(25.0)
(-20.4)
(-19.8)
(-4.7)
(24.7)
(61.4)
(-2.9)
C O 2 Reduction Potential (thousand ton-C O 2 /year)
(21.1)
T t ti C l i
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Keio University/Tsingua University 22
Tentative Conclusion
• Potential CO2 emission reduction in five major sectors isaround 100 Mt (Physical potential)
• Among them, power generation sector is the largest
(especially at 300 MW units)• When considering cost, picture changes drastically
• Very few commercially viable projects exist (at zero cost,
total reduction will be only 10 Mt, at $4.5, still 16 Mt evenunder our baseline emission figures)
• Fuel switching projects in power sector will not be
feasible due to high cost of natural gas• Public funding is essential for promotion of CDM projects
in China
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Keio University/Tsingua University 23
Further works
• Elaborate baseline emissions in view of
discussions at the Executive Board• Revisiting selection of model plants
• Improve data quality (other than power plants)
• Compare with other top down models
• Take into consideration of transaction
costs• Explore applicability of our methodology to
other developing countries