基于SMO算法的模糊PID负载频率控制性能研究  

Performance comparison of fuzzy PID load frequency control based on SMO algorithm

作　　者：吴海伟 徐柳飞 杨丹琳[2,3] WU Hai-wei;XU Liu-fei;YANG Dan-lin(State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 210024,China;State Grid Nanjing NARI Group Company(State Grid Electric Power Research Institute),Nanjing 211106,China;Guodian Nari Technology Co.,Ltd.,Nanjing 211106,China)

机构地区：[1]国网江苏省电力有限公司,南京210024 [2]国网南京南瑞集团公司(国网电力科学研究院),南京211106 [3]国电南瑞科技股份有限公司,南京211106

出　　处：《信息技术》2020年第6期162-167,共6页Information Technology

摘　　要：针对双区域互联电力系统中的负载频率控制(LFC)问题,文中比较了基于模糊逻辑的不同隶属函数的比例积分微分控制器(FPID)。采用蜘蛛猴优化(SMO)算法对控制器参数进行优化,使用再热式燃气轮机系统的线性化模型,结合发电率约束(GRC)和调速器死区(GDB)等非线性因素对研究进行了扩展。实验结果表明,在阶跃负载扰动(SLP)为1%的情况下,SMO算法在峰值欠冲、峰值过冲、稳定时间以及联络线潮流偏差等方面均优于粒子群优化(PSO)和基于"教与学"优化(TLBO)算法。In order to solve the load frequency control(LFC)of two area interconnected thermoelectric system,the proportion integral differential controller(FPID)is compared based on different membership functions of fuzzy logic.Spider monkey optimization(SMO)algorithm is used to optimize the parameters of the controller,and the linearization model of reheat gas turbine system is used to expand the research with the nonlinear factors such as power generation rate constraint(GRC)and governor dead zone(GDB).Experimental results show that SMO algorithm is superior to PSO and tlbo in peak undershoot,peak overshoot,stability time and tie line power flow deviation when the step load disturbance(SLP)is 1%.

关 键 词：模糊PID控制器 模糊隶属函数 负载频率控制 蜘蛛猴优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]