基于改进遗传算法的电力系统无功优化  

Reactive power optimization of power system based on improved genetic algorithm

作　　者：周晓娟 蒋炜华[2] 马丽丽[3] 

机构地区：[1]河南机电学校电子工程系,河南郑州450002 [2]河南机电高等专科学校电气工程系,河南新乡453002 [3]安阳供电公司,河南安阳455000

出　　处：《电力系统保护与控制》2010年第7期37-41,共5页Power System Protection and Control

摘　　要：将遗传算法应用于电力系统无功优化。针对传统遗传算法中存在的易陷入局部最优解和后期收敛速度慢的问题,在简单遗传算法(SGA)的基础上,提出更加有效的算法即改进遗传算法(IGA)。新算法结合灵敏度分析产生原始个体替代SGA。SGA的交叉和变异被改进,改进的交叉操作拥有快速局部调节能力,改进的变异操作引入灵敏度分析产生新的个体。所提算法在一个算例上进行了分析验证。Genetic algorithm is applied to reactive power optimization in this paper. Premature convergence and weak local optimization are two key problems existing in the conventional genetic algorithm. A more effective method--the improved genetic algorithm is put forward based on simple genetic algorithm（SGA）. The new algorithm combines sensitivity analysis to generate initial generation of individuals instead of SGA. The crossover and mutation operation of SGA are improved in the IGA, the improved crossover operation is in possession of the ability of fast local adjustment, the improved mutation operation combines sensitivity analysis to generate new individuals. In the end, the proposed approach is examined in one testing system.

关 键 词：传统遗传算法 无功优化 灵敏度分析 交叉 变异 

分 类 号：TM714[电气工程—电力系统及自动化]