基于多目标飞蛾算法的电力系统无功优化研究

发布时间：2018-03-06 22:35

  本文选题：多目标优化　切入点：进化算法　出处：《计算机科学》2017年S2期 　论文类型：期刊论文

【摘要】：鉴于电力需求的日益增长与传统无功优化方法的桎梏,如何更加合理有效地解决电力系统的无功优化问题逐渐成为了研究的热点。提出一种多目标飞蛾扑火算法来解决电力系统多目标无功优化的问题,算法引入固定大小的外部储存机制、自适应的网格和筛选机制来有效存储和提升无功优化问题的帕累托最优解集,算法采用CEC2009标准多目标测试函数来进行仿真实验,并与两种经典算法进行性能的对比分析。此外,在电力系统IEEE 30节点上将该算法与MOPSO,NGSGA-Ⅱ算法的求解结果进行比较分析的结果表明,多目标飞蛾算法具有良好的性能,并在解决电力系统多目标无功优化问题上具有良好的潜力。
[Abstract]:In view of the increasing demand for electricity and the shackles of traditional reactive power optimization methods, How to solve the problem of reactive power optimization in power system more reasonably and effectively has gradually become a hot topic. A multi-objective moth-fighting algorithm is proposed to solve the problem of multi-objective reactive power optimization in power system. The algorithm introduces fixed size external storage mechanism, adaptive mesh and filter mechanism to effectively store and enhance the Pareto optimal solution set of reactive power optimization problem. The algorithm uses CEC2009 standard multi-objective test function to carry out simulation experiments. The performance of the algorithm is compared with that of two classical algorithms. In addition, the results of comparison between the algorithm and the MOPSONNGSGA- 鈪，

本文编号：1576817