基于粒子群优化算法和动态调整罚函数的最优潮流计算(英文)  

Optimal Power Flow Using Particle Swarm Optimization and Non-Stationary Multi-Stage Assignment Penalty Function

作　　者：赵波[1] 郭创新[1] 曹一家[1] 

机构地区：[1]浙江大学电气工程学院,杭州310027

出　　处：《电工技术学报》2004年第5期47-54,共8页Transactions of China Electrotechnical Society

基　　金：This project supported by National Natural Science Foundation of China(No.60074040,60225006).

摘　　要：在电力市场环境下,诸多问题(例如实时电价,网络阻塞等)都需要最优潮流作为理想的工具。本文应用了一种简单有效、且收敛性很好的演化计算算法——粒子群优化算法(PSO)进行最优潮流问题的求解。在求解过程中,根据约束条件的越界量大小,动态的调节其罚函数,避免其收敛到局部最小点。应用此算法对IEEE30节点系统进行最优潮流计算,并且与线性规划和遗传算法进行了比较,结果表明该算法能够更好的获得全局最优解,具有实用意义。This paper presents the solution of the optimal power flow (OPF) using particle swarm optimization (PSO) technique. The main goal of this paper is to verify the viability of using PSO problem composed by the different objective functions. Incorporation of non-stationary multi-stage assignment penalty function in solving OPF problem can significantly improve the convergence and gain more accurate values. The proposed PSO method is demonstrated and compared with linear programming (LP) approach and genetic algorithm (GA) approach on the standard IEEE 30-bus system. The results show that the proposed PSO method is capable of obtaining higher quality solutions efficiently in OPF problem.

关 键 词：最优潮流 粒子群优化算法 动态调整罚函数 

分 类 号：TM744[电气工程—电力系统及自动化]