基于改进粒子群优化算法的配电网络重构

提出了一种求解配电网络重构的改进粒子群优化（PSO）算法。结合配电网络的特点改进了PSO算法粒子位置的更新规则，提高了迭代过程中有效解的产生概率；并结合禁忌（Tabu）搜索的记忆功能和藐视准则，克服了PSO算法的早熟问题。算，其结果与最优解吻合，证实了算法的有效性，并与较，表明了算法具有更好的搜索效率。最后对3个典型IEEE测试系统进行优化计Tabu搜索算法和遗传算法的计算结果相比

Modified Particle Swarm Optimization for Reconfiguration of Distribution Network

A modified particle swarm optimization (PSO) approach to solve the distribution network reconfiguration problem is presented. By modifying the rule of position updating considering the features of distribution network, the probability of producing feasible solutions is improved. The premature convergence problem of basic PSO is avoided by integrating tabu list and aspiration criterion into PSO. The optimization calculations of three typical IEEE testing systems by the presented method are conducted and the calculation results are compared with those by tabu search algorithm and genetic algorithm respectively. The comparison results demonstrate the validity and effectiveness of the proposed method.