Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm

被引:52
作者
Xiong Hugang [1 ]
Cheng Haozhong [1 ]
Li Haiyu [2 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200030, Peoples R China
[2] Univ Manchester, Dept Elect Engn, Manchester M13 9PL, Lancs, England
关键词
MOAIA; ORPF; voltage stability margin; adaptive crossover and mutation rate; global affinity; partial affinity;
D O I
10.1016/j.enconman.2007.09.005
中图分类号
O414.1 [热力学];
学科分类号
摘要
People have paid more attention to enhancing voltage stability margin since voltage collapses happened in some power systems recently. This paper proposes an optimal reactive power flow (ORPF) incorporating static voltage stability based on a multi-objective adaptive immune algorithm (MOAIA). The main idea of the proposed algorithm is to add two parts to an existing immune algorithm. The first part defines both partial affinity and global affinity to evaluate the antibody affinity to the multi-objective functions. The second part uses adaptive crossover, mutation and clone rates for antibodies to maintain the antibodies diversity. Hence, the proposed algorithm can achieve a dynamic balance between individual diversity and population convergence. The paper describes ORPF's multi-objective functional mathematical model and the constraint conditions. The problems associated with the antibody are also discussed in detail. The proposed method has been tested in the IEEE-30 system and compared with IGA (immune genetic algorithm). The results show that the proposed algorithm has improved performance over the IGA. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1175 / 1181
页数:7
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