一种改进PSO算法在经济调度中的应用研究

粒子群优化算法是一类新的基于群体智能的启发式全局优化技术,群体中的每一个粒子代表待解决问题的一个候选解,算法利用粒子之间的相互作用发现复杂问题解空间的最优候选区域.综述了算法的基本形式及其多种改进形式,通过比较提出了一种用于求解一般形式的非连续、非凸、非线性约束优化问题的改进粒子群算法,用于求解复杂的非凸、非线性电力系统经济负荷分配问题.仿真结果表明,所提出的方法搜索速度快,求解精度高,易于掌握,是解决电力系统经济负荷分配问题的有效手段.

Research on Application of an Improved Particle Swarm Optimization Algorithm to Economic Dispatch of Power Systems

Particle swarm optimization(PSO)is a new heuristic global optimization technique based on swarm intelligence.Each particle of the swarm represents one candidate solution of the problem being optimized.The algorithm finds optimal regions of complex problem spaces through the interaction of improved.The basic version and many kinds of improved versions of PSO are summarized;and a new versatile optimization called enhanced particle swarm optimization algorithm(EPSO) is presented by comparison.The algorithm can be used to solve the discontinuous,nonconvex,nonlinear constrained optimization problems.The economic dispatch(ED) problem of power system is solved by this algorithm.Simulation results show that chaotic optimization method for economic dispatch of power systems is not only fast,but also simple and effective.