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《Journal of Shanghai Jiaotong University》 2005-S1
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The Minimal Expectant Regret Concerned Electric Power Network Planning under Flexible Constraints

ZHAI Hai-bao1, CHENG Hao-zhong1, CHEN Chun-lin2, JIANG Feng-qing2, FANG Ling-feng2(1. School of Electronic, Information and of Electrical Eng., Shanghai Jiaotong Univ., Shanghai 200030, China; 2. Dept. of Development and Planning, Shanghai Municipal Electrical Power Company, Shanghai 200122)  
A multi-scenarios method was used to deal with the uncertainty of electrical source and load. The minimal expectant regret of invest between the expansion plan and the optimal plan in each scenario is defined as the object, and the flexible constraints are also concerned. The penalty function of overloads under N-1 criterion is another object. Based on the case of no original feasible solutions needed and high efficiency, the improved ant colony algorithm is used to solve this problem. The simulation results of an 18-bus system show that this method can, under flexible constraints, give the robust and flexible plan with the least expectant waste of investment.
【Fund】: 国家自然科学基金资助项目(50177017);; 高等学校优秀青年教师教学科研奖励计划资助
【CateGory Index】: TM715
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【References】
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【Co-references】
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1 Wang Mianbin1 Tan Zhongfu1 Zhang Rong2 Wang Chengwen1 Cao Fucheng1 Li Xiaojun1 (1. North China Electric Power University Beijing 102206 China 2. Beijing Jingchuang Xingye Investment Consultants Beijing 100043 China);Risk Evaluation Model of the Power Grid Investment Based on Increment Principle[J];Transactions of China Electrotechnical Society;2006-09
2 Gu Yongdong (Qidong Urban Power Company);Particle Swarm Optimization and Its Use in Transmission Network Expasion Planning[J];Electrotechnical Application;2007-02
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【Secondary References】
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1 SUN Qiang1,ZHANG Yun-zhou1,LI Jun1,WANG Le1,ZENG Yuan2(1.State Grid Energy Research Institute,Beijing 100761,China;2.State Power Economic Research Institute,Beijing 100761,China;3.Key Laboratory of Power System Simulation and Control of Ministry of Education,Tianjin University,Tianjin 300072,China);Risk Assessment Application in Power Grid Planning[J];Proceedings of the Chinese Society of Universities for Electric Power System and its Automation;2009-06
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