基于改进引力搜索算法的无功优化仿真研究  

Research on simulation of reactive power optimization based on improved gravitational search algorithm

作　　者：陈功贵[1] 刘利兰[1] 郭艳艳[2] 郭飞[1] 

机构地区：[1]重庆邮电大学自动化学院,重庆400065 [2]武汉铁路职业技术学院,机车车辆工程系,湖北武汉430205

出　　处：《实验技术与管理》2016年第5期113-116,120,共5页Experimental Technology and Management

基　　金：重庆邮电大学教育教学改革项目(XJG1522);重庆市研究生教改项目(yig143061)

摘　　要：针对引力搜索算法(GSA)在求解电力系统无功优化时出现早熟收敛和局部搜索能力差的问题,引入粒子群算法的记忆功能和加速机制,形成改进引力搜索算法(IGSA)。将GSA和IGSA基于Matlab对IEEE30节点测试系统进行电力系统无功优化仿真。仿真结果表明:IGSA算法避免了早熟现象,增强了局部搜索能力,能获得质量更高的最优解。该仿真实验可加深学生对电力系统无功优化的理解和对智能算法的认识。Gravitational search algorithm（GSA）is easy to convergence prematurely and has the poor local search ability when solving reactive power optimization problem.Thus,improved gravitational search algorithm（IGSA）is formed by introducing the memory function and acceleration mechanism of PSO based on basic GSA.GSA and IGSA have been examined and tested in IEEE30 bus test system for solving reactive power optimization based on Matlab software.Simulation results reveal that IGSA can avoid prematurity phenomenon,enhance local search ability and obtain the optimal solution with higher quality.The simulation experiment can deepen students＇ understanding for reactive power optimization and intelligent algorithms.

关 键 词：无功优化 引力搜索算法 MATLAB 电力系统仿真 

分 类 号：TM732[电气工程—电力系统及自动化]