关键词: 最优潮流, 粒子群优化算法, 混沌, 收敛, 局部最优, 最优化

Abstract: The market revolution of the power industry presents higher requirement for the computing precision and speed of Optimal Power Flow（OPF）.Contrasting to some of the classical algorithm in the past，it introduces the Particle Swarm Optimization（PSO） to deal with the fuel cost of the generating company in the analysis of optimal power flow theory and on the basis of the algorithm.But when taken into account the traditional PSO algorithm processing OPF restrictive conditions，the random particles can not guarantee the quality of the individual and the choice of its rate，and the convergence rate of the particle can be slow，in addition，it is so easy to fall into the local optimal solution that can not be recognized by people，so the improved chaotic particle swarm algorithm is presented.It makes use of the characteristic of chaos to improve the basic particle swarm optimization.This paper compares the chaotic particle swarm algorithm with the other nonlinear inequality constraints optimal algorithm analysis by testing with computer.The results of the example——the standard IEEE 5—bus system model showes that the improved chaos particle swarm optimization algorithm can be better dealt with optimal power flow constraints in dealing with the issue of optimal power flow.This method can also find preferable results and its correctness and validity is proven by a series of tests and computations，and that the algorithms can be widely applied to the areas of power system planning and operation.

Key words: optimal power flow, particle swarm optimization, chaotic, convergence, the local optimal, optimization