摘要
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。最后对3个典型IEEE测试系统进行优化计算,其结果与最优解吻合,证实了算法的有效性,并与Tabu搜索算法和遗传算法的计算结果相比较,表明了算法具有更好的搜索效率。
A modified particle swarm optimization （PSO） approach to solve tiae dirstribution networkreconfiguration 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.
出处
《电力系统自动化》
EI
CSCD
北大核心
2006年第7期27-30,79,共5页
Automation of Electric Power Systems
关键词
配电网络重构
粒子群优化算法
禁忌搜索算法
distribution network reconfiguration
particle swarm optimization
tabu search algorithm
