基于改进PSO算法的电力系统无功优化

粒子群优化PSO(Particle Swarm Optimization)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(Modified Particle Swarm Optimization)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。

Power system reactive power optimization based on modified particle swarm optimization algorithm

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.