基于改进免疫算法的PMU多目标优化配置  

Multi-objective Optimal PMU Placement Based on Animproved Immune Algorithm

作　　者：张健[1] 李国庆[2] 冀瑞芳[2] 

机构地区：[1]吉林省电力有限公司调度通信中心,吉林长春130021 [2]东北电力大学电气工程学院,吉林吉林132012

出　　处：《东北电力大学学报》2011年第4期38-42,共5页Journal of Northeast Electric Power University

摘　　要：为保证配置同步相量测量单元(PMU)的安装数目最小,且系统的N-1量测可靠性尽量高,以实现电网最大的网络结构可观测性,对PMU进行多目标优化配置。将经改进的免疫算法与帕雷托(Pareto)分类排序技术相结合,完成对进化个体解的评价,采用模糊集理论提取出最优折中解,并通过非一致性变异操作来提高免疫算法的性能。IEEE-39节点系统计算结果表明该方法可实现全局多目标寻优,得到多种合理的PMU优化配置方案。For a power grid to be completely observable when employing a minimal number of placed phasor mea-surement units（PMU）to achieve the highest reliability of the N-1 measurements,we optimize this PMU multi-objective placement problem,and take the Pareto non-dominated sorting mechanism integrated with the improved immune algorithm in order to evaluate evolutionary individual.Moreover,fuzzy set theory is employed to extract the best compromise non-dominated solution.and by non uniform mutation operator to improve the immune algorithm performance.The calculation results of IEEE-39 node system shows that this method can achieve the global multi objective optimization,and get more reasonable PMU configuration optimization scheme.

关 键 词：相量测量单元(PMU) 可观测性 多目标优化 免疫算法 

分 类 号：TM764[电气工程—电力系统及自动化]