基于改进灰狼算法的PMU最优配置方法  

Optimal PMU placement method based on improved grey wolf optimizer

作　　者：崔健 李升[1] 郁嘉炜 CUI Jian;LI Sheng;YU Jia-wei(Nanjing Institute of Technology,Nanjing 211167,China)

机构地区：[1]南京工程学院,南京211167

出　　处：《信息技术》2021年第8期75-80,共6页Information Technology

基　　金：江苏省大学生创新创业训练重点项目(202011276009Z)。

摘　　要：基于GPS的同步相量测量单元(PMU)的出现,为电力系统的实时监测和状态估计提供了可靠保证。针对PMU的最优配置问题,文中以确保系统结构完全可观测性和PMU配置数量最少为约束条件,提出了一种基于改进灰狼算法的PMU最优配置方法。改进算法在灰狼算法的基础上,采用Tent混沌序列改善其初始化,引入螺旋式数学模型提高其收敛速度,同时结合模拟退火算法思想弥补灰狼算法易陷入局部最优解的缺陷。应用改进算法在IEEE14节点系统和新英格兰39节点系统进行仿真计算,与遗传算法、粒子群算法和灰狼算法的仿真结果进行比较,说明了改进算法的优势。The appearance of synchronous phasor measurement unit(PMU)based on GPS provides reliable guarantee for real-time monitoring and state estimation of power system.Based on the problem of PMU optimal configuration,this paper proposes a PMU optimal configuration method based on improved grey wolf optimizer,which ensures the observability of full network and the number of PMU is minimum.On the basis of grey wolf optimizer,tent chaotic sequence is used to improve its initialization,and spiral mathematical model is introduced to improve its convergence speed.At the same time,the simulated annealing algorithm is combined to make up for the defect that grey wolf optimizer is easy to fall into local optimal solution.The improved algorithm is applied to IEEE 14 bus system and New England 39 bus system to do simulation calculation.The simulation results are compared with those of genetic algorithm,particle swarm optimization algorithm and grey wolf optimizer,which shows the advantages of the improved algorithm.

关 键 词：相量测量单元 PMU最优配置 可观测性 改进灰狼算法 

分 类 号：TM93[电气工程—电力电子与电力传动]