摘要
以电力系统状态完全可观测和相量测量单元PMU配置数目最小为优化目标,基于PMU的功能特点和电力网络的拓扑结构信息,形成快速且通用的电网拓扑可观测性判别方法,并设计了一种结合免疫系统信息处理机制的二进制粒子群优化算法对目标函数进行求解,该算法综合了粒子群优化算法简单快速和免疫系统种群多样性的优点,明显改善了进化后期算法的收敛性能和全局寻优能力。最后通过对IEEE14和新英格兰39母线系统进行PMU优化配置仿真及量测冗余性分析,验证了本文方法的有效性和优越性。
The optimal phasor measurement unit （PMU） placement problem is formulated as guaranteeing full power network observability and having minimum number of PMU in this paper. A speedy and general analysis method of power network topology observability is studied based on properties of PMU and topological structure information of the power network, and an improved binary particle swarm optimization algorithm combined with the information processing mechanism of immune system is proposed to solve the optimization problem. The proposed algorithm has both the properties of the speed advantage in binary particle swarm optimization and the diversity of antibodies in immune system, and the abilities of converging and seeking the global optimum results in later evolution process are improved observably. The effectiveness and superiority of the proposed algorithm is demonstrated with PMU placement optimization simulation and redundancy measurement analysis using IEEE14-bus system and New England 39-bus system.
出处
《电工技术学报》
EI
CSCD
北大核心
2008年第6期119-124,共6页
Transactions of China Electrotechnical Society
基金
江西省教育厅科技研究基金资助项目(2007188)
关键词
PMU最优配置
拓扑可观测性
二进制粒子群优化
免疫系统
Optimal PMU placement, topology observability, binary particle swarm optimization（BPSO）, immune system
