Load flow studies based on a new Particle Swarm Optimization

N. K. Jain, U. Nangia, U. Kumar
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引用次数: 2

Abstract

In this paper, an attempt has been made to develop a new variant of Particle Swarm Optimization (PSO) algorithm and perform load flow on IEEE 5 and 14 bus systems using this new algorithm. In this new PSO, a better population of particles is selected by applying reduction factor (r) after suitable number of iterations called sorting frequency (fs). This better population is based on the objective function value and is chosen after suitable sorting frequency. The results of load flow using the new PSO are found to be as accurate as that obtained by Newton Raphson method and are also found to converge faster than the conventional PSO.
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基于粒子群优化的潮流研究
本文尝试开发一种新的粒子群优化算法(PSO),并利用该算法在ieee5和ieee14总线系统上进行负荷流计算。在该粒子群算法中,在适当的迭代次数(称为排序频率(fs))后,通过应用缩减因子(r)来选择更好的粒子群。这个更好的种群是基于目标函数值,并在合适的排序频率后选择。结果表明,新粒子群算法与牛顿-拉夫森算法的计算精度相当,且收敛速度快于传统粒子群算法。
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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