基于小生境优化的变权重粒子群算法在PMU优化配置中的应用  

Application of Variable Weights Particle Swarm Optimization Algorithm Based on Niche Genetic Algorithm in PMU Placement

作　　者：张思为[1] 牛胜锁[1] 梁志瑞[1] 张建华[1] 苏海锋[1] 

机构地区：[1]新能源电力系统国家重点实验室,华北电力大学,河北保定071003

出　　处：《陕西电力》2012年第4期34-38,81,共6页Shanxi Electric Power

摘　　要：针对相量测量单元优化配置问题展开研究,提出了一种基于小生境优化的变权重粒子群算法来解决该问题。所提算法以离散粒子群算法为基础,通过基于共享函数的小生境技术优化初始粒子群,改进权重系数的取值函数来提高算法的收敛效果,最后进行冗余度比较得出最优方案。该算法与常用算法相比,提高了计算的收敛速度和全局性,实现了算法多峰性,可通过分析问题模型有效得出相量测量单元(PMU)优化配置方案。并通过IEEE 14母线系统和新英格兰39母线系统仿真实例验证了所提方法的有效性。This paper presents a variable weights particle swarm optimization algorithm based on niche genetic algorithm to solve the problem of optimal phasor measurement unit （PMU） placement. The algorithm is based on discrete particle swarm optimization algorithm. This paper applies niche genetic algorithm to improve initial particle swarm and optimizes weight coefficient function to improve convergence effect. Compared with the general algorilhm, the algorithm presented hy this paper improves convergence speed and global search effect and achieves muhi-peak effect. This hybrid algorithm can achieve the programs of PMU placement by analyzing system model effectively. The effectiveness of algorithm is verified by numerical calculation resuhs of IEEE-14 system anti New England 39-tins system.

关 键 词：相量测量单元 可观测 变权重粒子群算法 小生境技术 权重系数 冗余度 PMU 

分 类 号：TM76[电气工程—电力系统及自动化]