关键词: 电力系统无功优化, 差分进化算法, 粒子群算法, 静态稳定电压裕度

Abstract:

This paper establishes a three-objective hybrid algorithm,which takes into account of loss minimization,voltage level best target and maximum static voltage stability margin.The Cauchy particle swarm optimization (CPSO) algorithm is proposed and applied to IEEE-14 node system for three-objective reactive power optimization.Cauchy particle swarm optimization (CPSO) is basic particle swarm algorithm to join the Cauchy distribution,for each generation of the particle's velocity,position,and Cauchy mutation adaptive value,thereby increasing the diversity of population.When the population diversity is very poor,Cauchy mutation is performed by particles to cross in order to expand the search space,improve the population diversity and avoid premature convergence,thereby avoiding the problem of algorithm trapped in local optimal solution with improved convergence speed.By testing data and comparing rate of convergence,accuracy and global searching ability of the new algorithm,CPSO algorithm is found to be superior to the conventional DE algorithm and PSO algorithm.The results show the validity of the proposed model and algorithm,which has important theoretical guiding significance for the security and economic operation of power system.

Key words: power system reactive power optimization;differential evolution algorithm;particle swarm optimization algorithm;static voltage stability margin