Improved particle swam optimization algorithm for OPF problems

B. Zhao, C.X. Guo, Y. J. Cao
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引用次数: 67

Abstract

This work 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 nonstationary multistage assignment penalty function in solving OFF problems 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 OFF problem.
OPF问题的改进粒子游优化算法
本文提出了用粒子群优化技术求解最优潮流的方法。本文的主要目的是验证由不同目标函数组成的粒子群问题的可行性。在求解OFF问题时引入非平稳多阶段分配惩罚函数,可以显著提高收敛性,得到更精确的值。在标准的IEEE 30总线系统上对所提出的粒子群算法进行了验证,并与线性规划(LP)方法和遗传算法(GA)方法进行了比较。结果表明,所提出的粒子群算法能够有效地获得高质量的OFF问题解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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