Download - Updates on the Chinese Energy Sector
Updates on the Chinese Energy Sector
Yanjia Wang, Alun Gu, Aling Zhang
Tsinghua University, China
EASS Workshop
23rd September 2010, Beijing
Part A: Targets, Efforts and Results
WANG, Yanjia [email protected]
Part B: China LEAP Modeling Efforts
GU, Alun [email protected]
Targets
• National 11th Five-Year Plan(2006-2010): 20% reduction of energy intensity of GDP 10% reduction of pollutant emission
• National 12nd Five-Year Plan(2011-2015): may be another 20% EE
• Commitment to Copenhagen (2006-2020): 40-45% of reduction of carbon intensity of GDP
Efforts
• Adjust economic structure
• Improve energy efficiency
• Develop low-carbon energy resources
Energy Intensity of Value-added
EI (current price)calorific value
calculation coal equivalent
calculation
Primary 0.21 0.29
Secondary 1.58 1.50
Tertiary 0.45 0.60
EI (2005 constant price)calorific value
calculation coal equivalent
calculation
Primary 0.25 0.34
Secondary 1.74 1.65
Tertiary 0.50 0.67
Data before census
A Long Way To Go …
12. 2 11. 3 11. 1 11. 3
47. 7 48. 7 48. 5 48. 6
40. 1 40 40. 4 40. 1
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2005 2006 2007 2008
Comp
osit
ion
of G
DP
Ter t i arySecondaryPr i mary
Source: China Statistical Yearbook 2009(measured by current price)
Achieve EE target heavily relay on structure changed, but..
Direct Input Coefficient of Input-Output Table(2005)
Input Output Primary Secondary Tertiary
Primary 0.37920 0.06904 0.03317
Secondary 0.45264 0.76709 0.56483
Tertiary 0.16816 0.16388 0.40201
Source: China Statistical Yearbook 2009
Infrastructure construction consumed more energy-intensive products
0
200
400
600
800
1000
1200
1400
2000 2001 2002 2003 2004 2005 2006 2007 2008
Steel (Mt )
Cement (Mt )
Ethyl ene (10, 000t )
Chemi cal Fert i l i zer(100, 000t )
Source: China Statistical Yearbook 2001--2009
Energy Efficiency in Power Generation Plants
Measures: shut down small plants(200MW), build SC, USC power plants (600MW, 1000MW per generator)
Average coal i nput f or thermal power generat i on (gce/ kWh)
319
316
392
300
310
320
330
340
350
360
370
380
390
400
Mandatory Standards to Energy-intensive Products • Published norms of energy consumption per unit
product in various industrial sectors (affected on June 1st 2008).
• Including three levels of EE: for existing plants, for new-built plants and for targeted plants.
• Covered crude steel, ferroalloy, coke, cement, ceramics, flat glass, caustic soda, calcium carbide, synthetic ammonia, yellow phosphorus, copper, zinc, lead, nickel, tin, magnesium, antimony copper and copper-alloy tube, wrought aluminum alloy extruded profiles for architecture, electrolyzed aluminum.
• More norms are under development.
Award Energy Saving Projects
• Central government: 300 yuan/tce (savings ≥10,000tce/a)
• Some provincial government: 200-300yuan/tce (10,000 ≤savings ≥thousands)
• A few city government: 100yuan/tce
Efforts in Transport Sector
• Build mass transit and inter-city rapid transit system
• Consumption tax reduction(5% to 2.5%) to compact cars and hybrid cars (2009)
• Fuel tax on petrol consumption (2009) • Subsidy vehicle buyers if old car eliminated
(2009)• Mandatory limitation of vehicle ages• Fuel economy standards
Improving fuel efficiency by 19%
• GB19578-2004 Limits of Fuel Consumption for Passenger Cars– Stage I: effected July 1st 2005 for new certified cars;
July 1st 2006 for current produced cars– Stage II: effected January 1st 2008 for new certified
cars; January 1st 2009 for current produced cars
• Covered 2374 types of vehicles and 95 manufacturers in stage II, 444 types of vehicles (produced by 55 manufacturers) are failure to meet the standard. The manufacturers had to stop producing these 444 types of vehicles.
Traffic Makes Real Fuel Consumption Much Higher than the Standards
Source: Jin Yuefu (2005)
EE in Building Sector
• Appliance standards and labels
• Design standards for new buildings (big progress)
• Retrofit existing buildings (no progress)
• Monitoring governmental buildings (trial stage)
Saving Targets: 30%, 50% & 66%
• Regional based
• Baseline: 1980’s standard
• 30% saving standard: 1986
• 50% saving standards: 1996
• 65% savings standards: under development, effected in some regions.
Space-heating Standard in Beijing
Standards Average space-heating load (W/m2)
Heating system efficiency (%) Energy intensity (W/m2)Boiler house Network System
1980 31.7 55 85 46.75 67.8
30% 25.3 60 90 54 46.9
50% 20.6 68 90 61.2 33.7
65% 11.1 68 90 61.2 23.7
Source: Kang Yanbin 2008
More Specific Requirements (Beijing)
Building type Resident Office Business Department store Hotel
Elec. Cons. (kWh/M2 a) 18 53 88 200 87
Air conditioning 8 18 30 110 46
Lighting -- 14 22 65 18
Appliances -- 20 32 10 14
Elevators -- -- 3 14 3
Water system -- 1 1 0.2 5.8
Cooling (GJ/ M2 a) 0.29 (8 kWh/M2 a) 0.15 0.28 0.48 0.32
Heat (GJ/ M2 a) 2.33
(65.kWh/M2 a)
0.20 0.18 0.12 0.30
Hot water(GJ/ M2 person) -- -- -- -- 12
Source: 2009 Annual Report of Energy Conservation of Buildings
Wind Power Development
Wi nd Power I nstal l at i on Capaci ty (GW)
0. 76412
20
86
0
20
40
60
80
100
2004 2008 2009 2020
Solar Power Development
PV I nstal l at i on Capaci ty (GW)
0. 07 0. 140. 3
2
0
0. 5
1
1. 5
2
2. 5
2005 2008 2009 2020
Installed Capacity of Power Generation (1980 – 2008)
65.9
166.5
277.3
391.4
792.5
0
100
200
300
400
500
600
700
800
900
1980 1992 1998 2003 2008
Gig
aw
att
s
Mix of Installed Capacity of Power Generation(2008)
Hydro, 21.6%
Nuclear, 1.1%
Thermal, 75.9%
Other, 1.4%
Results Vs. Target
1
1. 05
1. 1
1. 15
1. 2
1. 25
1. 3
2005 2006 2007 2008 2009 2010
Energy Intensity of GDP (tce/10k RMB)
After census
Build Baseline
Economic census of 2008 conducted in 2009.
Revised GDP and energy data.
GHG inventory of 2005 is under development.
General Published Data Source1. Statistical Communiqué: Published by National
Bureau of Statistics (NBS) in February of Year X+1, using statistical data of January to November Year X and the growth rate of December Year X-1 to estimate GDP and energy of Year X.
2. Yearbook: Published by NBS in autumn of Year X+1 to present GDP and energy of Year X.
3. National Economic Census: Leading by State Council and NBS. Published in January of Year X+1. Conducted in Year X to investigate data of Year X-1. Once in every 4 years.
GDP Data
• Communiqué 2008 estimated GDP of 2008 was 30.067 trillion RMB.
• Yearbook 2009 adopted the same number (30.067 trillion RMB).
• GDP of 2008 was adjusted to 31.4045 trillion RMB after census, increased 4.45%.
• Communiqué 2009 estimated GDP of 2009 was 33.5353 trillion RMB.
GDP Adjustment – Big difference in service sector
Before census
After census
Discrepancy
GDP 30067 31404.5 1337.5 4.45%
First Industry
3400 3370.2 -29.8 -0.88%
Second Industry
14618.3 14900.3 282 1.93%
Tertiary Industry
12048.7 13134.0 1085.3 9.01%
Regular statistical system (Yearbook) collects value-added data mainly from
designated size of organizations Designated size of organization:
– Mining, Manufacture, Elec. Gas, Water: All state-owned and non-state-owned enterprises with annual revenue from principle business ≥5 million RMB
– Construction: various types of ownership with qualification certification and independent accounting systems
– Wholesale: Sales ≥20 million RMB; Employer (year-end)>20
– Retail: Sales ≥5 million RMB; Employer (year-end)>60– Hotel: rating stars– Catering: Sales ≥2 million RMB; Employer (year-
end)>40Other sectors: spot check
Census collects value-added data from all organizations
Wholesale, retail, hotel & catering
Yearbook Census Census/
Yearbook
(times)
Number of enterprises
138,086 1,403,000 10.16
Employee 11,374,819 18,912,000 1.66
Revenue 187,656.8 247,483 1.25
Total assets 75,118.3 121,619 1.62
Only collect gross output value from industrial enterprises by year
• Following former Soviet system, industrial enterprise accounting didn’t use the concept of value-add before 2009.
• The concept of value-add in constant price is even more difficult than for industrial enterprises.
• All value-add data for agriculture and industrial sectors are estimated by national and local statistical bureaus.
Key Energy Data Points • Statistical Communiqué on the 2008 National Ec
onomic and Social Development (issued on February 26th 2009) estimated total energy consumption of 2008 was 2.85 billion tce (coal equivalent calculation).
• China Statistical Yearbook 2009 (published in September 2009) adopted the same number(2.85 billion tce).
• Total energy consumption of 2008 was adjusted to 2.91 billion tce after census, increased 2.12%.
• Statistical Communiqué on the 2009 National Economic and Social Development (issued on February 25th 2010) estimated total energy consumption of 2009 was 3.10 billion tce.
Energy Yearbook 2009 revised energy consumption data from 2005 to 2007 based on the results of the 2nd national economic census in 2009
Version of Yearbook 2009 2008Discrepancy to 2nd
census (%)
2005 225781 214466 5.28
2006 247562 235156 5.28
2007 268413 253488 5.89
2008 277515 -- --
Primary Energy Consumption (10ktce, calorific value calculation )
Differences mainly in coal from 2nd censusSource: Energy Statistical Yearbook 2008, 2009
2007 Before census After census Discrepancy (%)
Primary EnergyConsumption(104tce)
253488 268413 5.89
Coal (104ton) 258641 272746 5.45
Petroleum (104ton) 36570 36659 0.24
NG(108cu.m) 695 705 1.47
Hydro power(108kWh)
4853 4853 0.00
Nuclear power(108kWh)
621 621 0.00
Energy Efficiency Improvement
Beforecensus
GDPConstantprice
EnergyConsumption(coal equivalentcalculation)
EIEIDecreaserate(%)
GDPCurrentprice
Inflation (%)
2005 183217.4 224682 1.23 183217.4 0
2006 204556.1 246270 1.20 1.83 212923.5 4.09
2007 231228.4 265583 1.15 4.60 257305.6 11.28
2008 252039 285000 1.13 1.55 300670 19.30
2009
SourceStatistical Yearbook2009
EnergyStatistical,Communiqué
Cal. Cal.Statistical Yearbook2009
Cal.
EI decreased 8.13% from 2005 to 2008.
Energy Efficiency Improvement
After census
GDP (constant price)
Energy Consumption (coal equivalent calculation)
EI
EIdecrease rate(%)
GDPcurrent price
Inflation (%)
2005 184937 235997 1.276 184937 0
2006 208442 258676 1.241 2.74 216314 3.78
2007 237920 280508 1.179 5.04 265810 11.72
2008 260687 291448 1.118 5.20 314045 20.47
2009 284680 306600 1.077 3.16 335353 17.80
Source:
Calculated by EI and energy consumption
Energy Statistical
NSBDocument2010
NSBDocument2010
CommuniquéCal.
EI decreased 12.38% from 2005 to 2008; decreased 15.6% from 2005 to 2009
Energy Efficiency Improvement
After census
GDP (constant price)
calorific value calculation coal equivalent calculation
Energy Consumption (% of hydro & nuclear)
EI Energy Consumption(% of hydro & nuclear)
EI
2005 184937 225781 (2.5) 1.221 235997 (6.8) 1.276
2008 260687 277515 (3.0) 1.065 291448 (7.7) 1.118
△2008-
2005
75750 51734 55451
EI decreased 2005 to 2008
12.78% 12.38%
1. Total energy consumption coal equivalent calculation based is not transparent since the data of coal consumption per kWh generated changed year by year and not be published formally.
2. Prefer to use coal-based number since it shows a bigger share of clean energy while 15% target was set by 2020.
3. May be change to use calorific-based number since it shows a big improvement on EI.
Part B: China LEAP Modeling Efforts
Basic Assumptions
• Base year: 2000 ->2005
• Target year: 2030
• Dataset: AES2007 Draft
• LEAP2008
• Three scenarios: BAU (considering regional cooperation), Maximum Nuclear Path(MaNS), Minimum Nuclear Path(MiNS)
• Data source
Per capita GDP
• China’s per capita GDP is expected to be quadrupled by the year 2020 as against 2000 in the report of 17th NCCPC on October 2007.
2000 yr: 7078 RMB (856 US$)
2020 yr: 28000 RMB (3500US$,
not considering rate fluctuation)
2006 yr: 2024 US$
• This goal is much higher than the target set by the CPC five years ago at the 16th National Congress which was to quadruple the GDP value, without the mention of per capita by 2020.
• But the rapid growth will be under the condition of reduced consumption of resources and greater efforts in environmental protection.
Per capita house area and urbanization
• Industrialization and urbanization have speeded economic development.
• Per capita income will increase and people living level will be improved.
• Although there is a big income gap between urban and rural residents, per capita house area is expected to be similar by 2050.
The urban-rural income disparity has been increased recently
Source: LI Shantong, 2006
Population and GDP assumptions
• The BAU scenario reflects a 20-year economic development path that yields average annual GDP growth rates of 8.38% between 2010 and 2020 and 7.11% between 2020 and 2030.
• China’s population forecast in the model, adopting national population plans and projections, shows the peak of total population arriving between 2030 and 2040, at 1.47 billion people, with continued and pronounced movement of population from rural to urban area.
Year Population (million persons)
Urban HH (million)
Rural HH (million)
GDP (108 yuan RMB)
2005 1308 190 183 183132 2010 1360 222 190 290505 2020 1440 288 181 649852 2030 1470 337 160 1291047
Nuclear power scenarios changesInstalledcapacity
(GW)share
Installedcapacity
(GW)share
Installedcapacity
(GW)share
S1 8.7 1.60% 25 3.50% 45 4.50%
S2 (BAU) 8.7 1.60% 20 2.80% 40 4.00%
S3 8.7 1.60% 15 2.10% 30 3.00%
2005 2010 2020
Installedcapacity
(GW)share
Installedcapacity
(GW)share
Installedcapacity
(GW)share
Maximum Nuclear Path 8.7 1.60% 25 3.5% 80 8%BAU 8.7 1.60% 15 2.1% 40 4%Minimum Nuclear Path 8.7 1.60% 12 1.7% 20 2%
2005 2010 2020
AES2006AES2006
AES2007 AES2007
2005 2010 2020 2030
Installed capacity
(GW)share
Installed capacity
(GW)share
Installed capacity
(GW)share
Installed capacity
(GW)share
Maximum Nuclear Path 8.7 1.60% 25 3.5% 80 8% 134 8%
BAU 8.7 1.60% 15 2.1% 70 7% 100 4%
Minimum Nuclear Path 8.7 1.60% 12 1.7% 60 6% 80 2%
AES2010 AES2010
Industry assumptions
• Based on China’s government policy, growth in the most energy-intensive industrial sectors will be controlled and mainly used to fulfill domestic needs, and energy efficiency measures will be implemented in those sectors to enhance energy savings.
• In the steel, cement, and pulp and paper sectors, for example, physical output is projected to rise through 2020, but then fall slightly (steel), remain unchanged (cement), or rise only slightly (pulp and paper) through 2030.
• At the same time, the energy intensities per unit physical product in these industries is projected, in the BAU path, to fall by 1.0 to 1.8% annually, varying by industry and time period (China Low Carbon Scenario, 2009).
Results for BAU Scenario
• BAU Scenario Energy Demand by Sector, 2000-2030
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4500
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Mill
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To
nn
es
Co
al E
qu
iv.
Agriculture
Transport
Commerce
Industry
Households
Results for BAU Scenario
• BAU scenarios transport energy demand, 2000-2030
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2000 2005 2010 2015 2020 2025 2030
Mill
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nn
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iva
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Passenger Transport
Freight Transport
Results for BAU Scenario
• BAU Scenario Final Energy Demand by Fuel, 2000-2030
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3500
4000
4500
2000 2005 2010 2015 2020 2025 2030
Mill
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nn
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iv.
Biomass Coal Coke and Peat
Crude Oil Electricity
Heat Natural Gas
Oil Products Other fuels
Renewables
Results for BAU Scenario
• BAU Energy Supply Outputs by Fuel, 2000-2030
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1500
2000
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3500
4000
4500
5000
2000
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Mill
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nn
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al E
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iv.
Other fuels
Oil Products
Natural Gas
Heat
Electricity
Crude Oil
Coal Coke and Peat
Biomass
Results for three Scenarios
• Greenhouse Gas Emissions, 2000-2030, Three Scenarios for China
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Mill
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nn
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CO
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qu
iv.
BAU Reference
Maximum nuclear path
Minimum nuclear path
Conclusions
• China has experienced rapid growth in energy consumption in the recent years. Large amounts of investment have been provided for the power industry and for oil stockpile facility construction to secure energy supplies to support rapid economic growth.
• To realize China’s sustainable development, the national energy development strategy includes an energy conservation priority policy, and at the same time is vigorously developing renewable energy and new energy in China. A cleaner energy system and energy development strategy are needed, and should be established through government involvement leading to changes in all production processes and lifestyles through the applications of laws, regulations and fiscal policies.
• Vehicle emission problems in particular require special attention, especially those associated with increases in freight and passenger transport energy consumption.