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Application of Pinch Analysis Approach to CO 2 Emission Constrained Energy Planning: Dingjiang Chen 1, Jianfeng Cai 1, Bing Zhu 1,2 1 Dept. of Chem. Eng.,

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Presentation on theme: "Application of Pinch Analysis Approach to CO 2 Emission Constrained Energy Planning: Dingjiang Chen 1, Jianfeng Cai 1, Bing Zhu 1,2 1 Dept. of Chem. Eng.,"— Presentation transcript:

1 Application of Pinch Analysis Approach to CO 2 Emission Constrained Energy Planning: Dingjiang Chen 1, Jianfeng Cai 1, Bing Zhu 1,2 1 Dept. of Chem. Eng., Tsinghua University 2 ENE Program, IIASA International Energy Workshop 17-19 June, 2009, Venice, Italy Targeting Minimum Low-carbon Energy Demand for China

2 2/20 Outline Introduction of pinch analysis approach Scenarios: the minimum low-carbon energy demand for China in 2030 with certain CO 2 emission constraints Study regional carbon trades with pinch analysis approach

3 3/20 Introduction of pinch analysis approach 1

4 4/20 Q Cmin To identify the bottleneck (pinch point) between the supply and the demand , so as to satisfy specific target with minimum utilities 。 Intuitive and with clear physical meaning Suitable for primary planning Can’t handle complicated constraints T H  T min Q Cmin supply demand bottleneck utility Graphical Pinch Analysis Heat Exchange Network Pinch Analysis

5 5/20 Pinch point Graphical Carbon Pinch Analysis Supply composite curve Demand composite curve Carbon pinch point Minimum low-carbon energy usage Extra high-carbon energy usage Energy (TJ) CO 2 emission (million tons) Energy demand composite curve Region I Region II Region III NG Oil Coal Minimum low-carbon energy usage Tan RR, Foo DCY. Pinch analysis approach to carbon-constrained energy sector planning. Energy, 2007,32(8):1422-1429. Energy supply composite curve Extra high-carbon energy usage CO 2 emission limit

6 6/20 To Construct Energy Supply Composite Curve Energy (TJ) CO 2 emission (million tons) NG Oil Coal SiSi C out,i S i C out,i

7 7/20 To Construct Energy Demand Composite Curve CO 2 emission (million tons) Region I Region II Region III DjDj C in,j D j C in,j aggregated energy demand composite curve

8 8/20 Regional CO 2 Emission Factor DjDj C in,j D j C in,j tg  C in,j  CO 2 emission limit of region j Energy consumption of region j What’s the rule to allocate share of total CO 2 emission limit to a region ? P - total populationC - total CO 2 emission limit P j - population of region j An example C j - CO 2 emission limit of region j E j (D j ) - energy consumption (Demand) for region j

9 9/20 Rules of Allocating Regional CO 2 Emission Limit CO 2 emission limit of region j (D j C in,j ) Regional CO 2 Emission Factor(C in,j ) According to Energy consumption (E) Population (P) GDP (G)

10 10/20 Is the Regional CO 2 Emission Allocation Rule Fair? Provinces in China Developing Areas Developed Areas (low) (high) Regional CO 2 Emission Factor(C in,j )

11 11/20 Scenarios: the minimum low- carbon energy demand for China in 2030 with certain CO 2 emission constraints 2

12 12/20 Aggregated Planning with Overall Emission Limits 1350 10220 5461 7 tons per capita CO 2 emission x 14.6 billion people Energy (Million Tons of Coal of Equivalent) CO 2 Emission (Million Tons) Data source of energy resource supply, demand, and estimated population : IEA. World Energy Outlook 2007. The Reference Scenario for China

13 13/20 1350 10220 5461 800 11680 Aggregated Planning with Overall Emission Limits 8 tons per capita CO 2 emission x 14.6 billion people Energy (Million Tons of Coal of Equivalent) CO 2 Emission (Million Tons)

14 14/20 1350 5461 800 580 Energy (Million Tons of Coal of Equivalent) CO 2 Emission (Million Tons) Aggregated Planning with Overall Emission Limits 8.4 tons per capita CO 2 emission x 14.6 billion people the CO 2 emission constraint that China can endure according to IEA’s reference scenario data

15 15/20 Disaggregated Planning with Individual Regional Emission Limits 5461 1350 1550 Data of China regional energy demand in 2030 are estimated from China Eenergy Statistical Yearbook 2007. Energy (Million Tons of Coal of Equivalent) CO 2 Emission (Million Tons) ~15% extra cost of low-carbon energy in order to satisfy each of the regional CO 2 emission limits

16 16/20 Study regional carbon trades with pinch analysis approach 3

17 17/20 To Reduce the Extra Low-Carbon Energy Cost through Regional Carbon Trade Regional carbon trade CC CC Energy CO 2 emission Regional Carbon Trade across pinch point CC Regional Carbon Trade above pinch point CC Regional Carbon Trade below pinch point

18 18/20 Implied policy preference –Encouraging reduction of energy consumption per GDP unit –However, more restriction to developing regions Beijing Guangdong Zhejiang Jiangsu Shanghai Fujian Hainan Jiangxi Tianjin Guangxi Anhui Shandong Henan Shanxi Hunan Chongqing Hubei Sicuan Heilongjiang Jilin Yunnan Liaoning Hebei Xinjiang Gansu Neimeng Shanxi Qinghai Guizhou Ningxia Energy (Million Tons of COE) CO 2 Emission (Million Tons)

19 19/20 Concluding Remarks The graphical carbon pinch analysis is intuitive for primary regional energy planning with CO 2 emission constraints. There is extra cost of low-carbon energy when to satisfy regional CO 2 emission constraints. Regional carbon trade may help reducing the extra cost. Policy to allocate regional CO 2 emission limit has to be carefully designed to make balance between economic development and carbon emission control.

20 Thanks for your attention!


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