Comprehensive Decision-Making of Power Planning Including Clean Energy and Low-Carbon Electricity Technology

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Abstract:

According to the characteristics of power planning, select four key planning scenarios, calculate the initial probability and simulation probability in sequence, and thus calculate the scenario probability. Define the screening considering the scenario probability and incidence of evaluation factor index for the typical scenario. In the decision-making process, the fuzzy decision method of interval numbers based on trapezoidal membership function is used to calculate the scheme membership, which overcomes the difficulty of precise calculation problem for planning index. And according to maximum membership degree for sorting, finally obtaining quality comparison results of the scenarios. As an example of a "twelfth five-year" planning of one city, an integrated decision making of power planning is developed, the simulation results show the scientificity and rationality of the method.

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1383-1387

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] GAO Ciwei, CHENG Haozhong, WANG Xu. The application of fuzzy evaluation of blind information in electric network planning [J]. Proeeedings of the CSEE, 2004, 24(9): 24-29.

Google Scholar

[2] KONG Xiang-yu, FANG Da-zhong. Uncertain Multi2Objective Generation Expansion Planning Model[J]. Journal of tianjin university, 2008, 41(2): 183-188.

Google Scholar

[3] ZHOU Jinghong, HU Zhaoguang, TIAN Jianwei, et al.A power integrated resource strategic planning model and its application[J]. Automation of Electric Power System, 2010, 34(11): 19-22.

DOI: 10.1109/pes.2010.5589971

Google Scholar

[4] XIE Chuansheng, DONG Da-peng, DUAN Kai-yan. Degree evaluation of low carbon power grid planning coordination based on the analytic hierarchy process - distance coordination degree[J]. Grid power technology, 2012, 36(11): 1-6.

Google Scholar

[5] YANG Gaofeng, KANG Chongqing, GU Xingkai, et al. Analysis based flexibility evaluation of power grid planning under deregulation[J]. Power System Technology , 2006, 30(14): 64-70.

Google Scholar

[6] GAO Ciwei, CHENG Haozhong, WANG Xu. Electric power network flexible planning model based on the probability of scene occurrence[J]. Proeeedings of the CSEE, 2004, 24(11): 34-38.

Google Scholar

[7] ZONG Bei-hua. The application of scenario method in port strategy[J]. Journal of Shanghai Maritime University, 1992(4): 28-34.

Google Scholar

[8] MA Liye, LU Zhigang, HU Huawei. Fuzzy comprehensive evaluation of economic operation in urban distribution network based on interval number[J]. Journal of electrical engineering technology, 2012, 27(8): 163-171.

Google Scholar