A Combination Strategy for Reactive Power Optimization Based on Model of Soft Constrain Considered Interior Point Method and Genetic-Simulated Annealing Algorithm

摘要：

In this paper a combination strategy for reactive power optimization is proposed. It bases on the optimal reasult of Genetic-Simulated Annealing Algorithm and Primal-Dual Interior Point(PDIP) Algorithm, and solves the problem of discrete and continuous control variables in reactive power optimization effectively. Simultaneity, it introduces the soft costraint to handle the infeasibility problem appearing in the course of reactive power optimization. Numeriacal simulation results on the IEEE57 and the IEEE118 test system show that the proposed method can brings up the speed and the convergence of computation, and illustrate that the proposed method can effectively handle and detect the infeasibility problem caused by bottleneck constraints and get a reasonable solution fast

关键词： Genetic-Simulated Annealing Algorithm Primal-Dual Interior Point Algorithm reactive power optimization the infeasibility problem soft constraint

作者: Guo Liya Ding Xiaoqun Chen Guangyu Song Jizhong Cui Qihui Liu Wenhua

作者单位: Dept. of Energy and Electrical HoHai University Nanjing, Jiangsu,China Shandong Dongying power company Dongying, Shangdong, China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 731-734

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）