【摘要】 粒子群优化PSO(ParticleSwarmOptimization)算法是一种简便易行、收敛快速的演化计算方法,但该算法也存在收敛精度不高,易陷入局部极值的缺点。针对这些缺点,对原算法加以改进,引入了自适应的惯性系数和变异算子,提出了一种新的改进粒子群优化MPSO(ModifiedParticleSwarmOptimization)算法,并将其应用于电力系统无功优化,建立了相应的优化模型。对IEEE-14节点系统及某地区70节点实际电力系统进行了仿真计算,并与PSO算法作了比较,结果表明MPSO优化算法能有效地应用于电力系统无功优化,其全局收敛性能及收敛精度均较PSO算法有了一定程度的提高。更多还原

【Abstract】 PSO (Particle Swarm Optimization) is an evolutionary computation technique,which is simplein application and quick in convergence,but also low in precision and easy in premature convergence. A modified algorithm MPSO(Modified Particle Swarm Optimization) is presented and applied to reactive power optimization of power system. Compared with PSO,the optimization results of IEEE-14-bus system and a real regional power system show that MPSO is a successful and feasible approach for reactive power optimization and the global convergency and convergence precision are better.更多还原