求解径向配电系统DG分配问题的对立布谷鸟优化算法

Santanu Roy, S. Sultana, P. Roy
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引用次数: 6

摘要

径向配电系统中分布式发电机组的优化尺寸和布局是目前研究的热点问题。本文采用布谷鸟优化算法(cuckoo optimization algorithm, COA)寻找DG的最优位置,以优化径向配电系统的功率损耗。此外,为了提高COA的收敛速度,引入了一种基于对立的学习(OBL)方法。通过对33总线和69总线径向配电系统进行优化,验证了该优化方法的有效性和高效性。仿真结果与遗传算法(GA)、粒子群算法(PSO)、遗传/粒子群优化算法(GA /PSO)、细菌觅食优化算法(BFOA)等基于种群的优化算法进行了比较,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Oppositional cuckoo optimization algorithm to solve DG allocation problem of radial distribution system
Optimal sizing and placement of distributed generator (DG) units in radial distribution system are becoming very attractive to researchers these days. In this paper, cuckoo optimization algorithm (COA) is applied in order to find the optimal location of DG to optimize the power loss in radial distribution system. Furthermore, an oppositional based learning (OBL) is introduced with COA for improving the convergence speed of COA. The proposed oppositional COA (OCOA) methodology is successfully applied to the 33 bus and 69 bus radial distribution systems in order to show the effectiveness and efficiency of this optimization. The simulation result of proposed methods are compared with the other population based optimization like genetic algorithm (GA), particle swarm optimization (PSO), GA/PSO, bacteria foraging optimization algorithm (BFOA) in order to show the usefulness of this proposed approach.
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