基于GIS和差分进化粒子群的变电站选址方法

文中提出了一种基于地理信息系统(GIS)和差分进化改进粒子群的配电网变电站优化选址方法。该方法利用GIS确定变电站数量,基于变电站投资运行费用建立有约束条件的目标函数,采用粒子群算法进行变电站选址优化。针对粒子群算法易陷入局部最优且收敛速度慢的问题,借助差分进化引入两个变异因子,在提升粒子群算法收敛速度的同时,避免其陷入局部最优。算例分析结果表明,该方法具有较好的寻优能力和收敛特性,能够有效实现变电站选址优化。

Substation locating based on differential evolution particle swarm optimization

An optimized method for substation locating based on geographic information system(GIS)and differential evolution improved particle swarm optimization is proposed.GIS is used to determine the number of substations,a constrained objective function is built based on substation investment operating costs,particle swarm optimization is used to optimize substation locating.To solve the problem that particle swarm optimization easily fall into local optimum and slow convergence speed,two mutation factors are introduced by differential evolution to improve the convergence speed of particle swarm optimization and avoid it falling into local optimum.The results show that the method has good searching ability and convergence characteristics,and can effectively realize the substation locating optimization.