基于混沌差异进化算法的有功优化仿真研究  

Research on active power optimization based on chaotic differential evolution algorithm

作　　者：陈功贵[1] 陆正媚 郭艳艳[2] 郭飞[1] 唐贤伦[1] 

机构地区：[1]重庆邮电大学自动化学院,重庆400065 [2]武汉铁路职业技术学院机车车辆工程系,湖北武汉430205

出　　处：《实验技术与管理》2016年第3期34-38,共5页Experimental Technology and Management

基　　金：重庆邮电大学教育教学改革项目(XJG1522;XJG1416);重庆市高等教育教学改革研究重点项目(132016)

摘　　要：差异进化(differential evolution,DE)算法在求解电力系统有功优化的问题上易陷入局部最优,因此在其基础上引入混沌算法的Logistic映射,形成混沌差异进化(chaotic differential evolution,CDE)算法。该算法在迭代后期,使固定取值的搜索步长和交叉算子在一定范围内随机取值。为验证算法的实用性,利用Matlab软件,将DE和CDE在IEEE30节点测试系统上进行电力系统有功优化仿真。仿真结果表明,CDE算法扩大了搜索范围并且增加了种群多样性,能获得搜索质量更高的最优解,即考虑阀点效应的燃料费用更低。通过此次仿真,既可加深学生对有功优化的认识和理解,又可提高学生运用仿真技术为改进算法提供理论依据与评价的能力。The differential evolution（DE）algorithm deals with the problem of active power optimization of power system easily to fall into local optimum,for this reason,it is combined with the Logistic mapping of the chaotic algorithm to form the chaotic differential evolution（CDE）algorithm.In later iterations,the search step and crossover of the chaotic differential evolution algorithm are changed from fixed value to a certain range of random value.In order to illustrate the practicability of algorithms,by the Matlab software,using the differential evolution algorithm and the chaotic differential evolution algorithm can implemente an active power optimization simulation on the IEEE30 bus test system.Simulation results show that the chaotic differential evolution algorithm expands the search range and increases the diversity of the population,so it can get the optimal solution of higher quality,namely it can get a lower fuel cost considering the effect of valve point.The simulation experiment can not only strengthen the students＇ understanding of active power optimization,but also improve their ability of using the computer technology to provide theoretical basis and evaluation for the improved algorithms.

关 键 词：电力系统仿真 有功优化 混沌差异进化算法 MATLAB 

分 类 号：TM732[电气工程—电力系统及自动化]