改进PSO算法解决电力系统机组优化组合问题

机组组合优化问题是一个大规模、离散、非线性的混合整数规划问题,所以求解比较困难,不容易找到理论上的最优解。本文在基本粒子群算法（PSO）的基础上,使用一种空间收缩策略,加快了算法的收敛速度。同时,为了避免算法出现“早熟”现象,让粒子不仅根据自身和同伴中的最好个体进行调整自己的飞行速度,并且向其他个体学习,以及通过改进的粒子群算法（MPSO）进行仿真计算,证明了该算法的有效性。

Modified PSO Algorithm for Power System Unit Commitment Optimization

Unit commitment is a large-scale,dispersed and non-linear hybrid integer programming problem.In this paper,a modified PSO mechanism is proposed to deal with the equality and inequality in the conventional PSO.And a dynamic search-space reduction strategy is devised to accelerate the optimization process.Also adjustment operator and adjustment sequence are introduced to reconstruct PSO algorithm by using the idea of single node regulating algorithm.Numerical simulation results show that the proposed method is effective.