基于改进粒子群优化算法的电力系统无功电压综合控制

Reactive power and voltage control based on improved particle swarm optimization in power system

在基本粒子群优化算法的基础上,提出了一种改进的粒子群优化算法用于电力系统无功电压综合控制。该算法改进了随机初始化种群的方法,采用均匀初始化,引进了粒子的自身探索机制,用多个位于可行域中的粒子个体引导粒子的更新,以保证全局搜索的有效性,同时采用混沌变异算子对陷入局部最优的粒子进行变异,提高了算法的寻优性能。通过对IEEE-30节点标准系统模型的无功电压综合控制计算和分析,证明了此改进的粒子群优化算法具有更高的全局寻优效率。

An Improved Particle Swarm Optimization（IPSO） algorithm applied to the Reactive Power and Voltage Control of power system （RPVC） is proposed followed by the Basic Particle Swarm Optimization（BPSO）. The algorithm changes the stochastic initialization with equality initialization and adopts a principle of particle searching by itself. Several particles in feasible solutions are used to lead swarm＇s motion and update. At the same time, the algorithm uses chaotic mutation factor to change positions of the particles which plunged in the local optimization. Simulation results of IEEE 30-bus power system show that the IPSO is more efficient than BPSO and some other optimization methods.