改进生物地理学优化算法在配电网无功优化中的应用  

Biogeography Improved Optimum Algorithm in Reactive Power Optimization

作　　者：王海燕[1] 胡泽浩 WANG Haiyan;HU Zehao(Shanghai University of Electric Power,Shanghai200090,China;State Grid Zhejiang Yiwu Power Supply Co.,Yiwu322000,China)

机构地区：[1]上海电力学院,上海200090 [2]国网浙江省义乌市供电公司,浙江义乌322000

出　　处：《上海电力学院学报》2018年第1期85-89,94,共6页Journal of Shanghai University of Electric Power

基　　金：上海市电站自动化技术重点实验室项目(13DZ2273800)

摘　　要：针对生物地理学算法(BBO)信息利用能力强但搜索能力不强的问题,提出了一种结合遗传算法改进变异操作的算法.改进算法充分利用了遗传算法的搜索能力,使算法的寻优能力得到了很大的改善.将该算法应用于IEEE34节点的系统,采用分区的方法进行无功补偿优化.算例表明:与基本BBO算法、遗传算法的无功优化相比,改进算法在计算速度和优化效果方面都具有明显的优势.In view of the fact that biogeography algorithm information utilization is strong but search is not,an improved algorithm is used to improve the operation of variation and genetic algorithm,the improved algorithm is called BBOGA algorithms.Because the improved algorithm makes full use of the genetic algorithm search capabilities,which is coupled with the ability to use the algorithm biogeography of information,so that the algorithm optimization capability can be greatly improved,it is used for reactive power compensation optimization IEEE34-node system,which is partitioned approach.The example shows that basic BBO improved algorithm,genetic algorithm compared to reactive power optimization has obvious advantages in terms of computational speed and optimization effect.

关 键 词：生物地理学算法 遗传算法 分区补偿 无功优化 

分 类 号：TM714[电气工程—电力系统及自动化]