电力系统无功优化自适应粒子群算法

针对粒子群(PSO)算法存在易陷入局部最优的缺点,提出了一种新的基于种群多样性指数的自适应粒子群优化算法(ASPO)。该算法利用种群多样性信息对惯性权重进行非线性调整,并在算法后期引入速度变异算子和位置交叉算子,使算法摆脱后期易于陷入局部最优的束缚,同时又保持前期搜索速度快特性。将其应用于电力系统无功优化,对IEEE-30节点系统进行仿真计算,并与GA、PSO等算法比较,结果表明APSO算法能有效应用于电力系统无功优化,其全局收敛性能、收敛精度和收敛稳定性均较GA、PSO算法有了明显提高。

Adaptive Particle Swarm Algorithm for Reactive Power Optimization of Power System

An adaptive particle swarm optimization algorithm(PSO)is presented to solve the problem that conventional PSO algorithm inclined to fall into partial optimization.A new method of adaptive particle swarm optimization algorithm(ASPO)based on population diversity is proposed.In this algorithm,inertia weight is nonlinearly adjusted by using population diversity information.And in the later stage of the algorithm,velocity mutation factor and position interchange factor are introduced to overcome the above defect...