基于改进社会认知算法的电力系统多目标无功优化  

Multi-objective reactive power optimization based on modified society cognitive optimization for electric power system

作　　者：白云[1] 徐刚刚[2] 宋阳[3] 

机构地区：[1]河南省电力公司洛阳供电公司,河南洛阳471029 [2]东北电力大学电气工程学院,吉林吉林132012 [3]吉林省电力有限公司长春供电公司,吉林长春130021

出　　处：《黑龙江电力》2012年第2期120-124,共5页Heilongjiang Electric Power

摘　　要：针对电力系统无功优化传统算法的局限性,结合当前智能算法的特点,提出采用模拟农夫捕鱼算法改进社会认知算法(ISCO),将其运用到电力系统无功优化中,并在构建无功优化的数学模型时,充分考虑如何降低网损和综合考虑减少电压偏差及提高系统运行的电压稳定裕度。经对标准IEEE14和IEEE30节点系统进行仿真计算,结果表明该算法具有很好的全局寻优能力和较快的收敛速度,能有效提高系统运行的经济性和安全性。According to the limitation of traditional reactive power optimization for electric power system and the characteristics of intelligent algorithm,this paper simulates fisher fishing for improving society cognitive optimization,which is applied in reactive power optimization for electric power system.The paper also takes how to reduce network loss and voltage deviation and enhance voltage stability margin into consideration when establishing mathematical model of reactive power optimization.The result of simulation of standard IEEE14 and IEEE30 node system proves that this algorithm enjoys high speed of global optimization and convergence and enhances the economy and security of system running.

关 键 词：社会认知算法 收缩搜索 多目标无功优化 

分 类 号：TM713[电气工程—电力系统及自动化]