三种粒子群算法在分布式发电机组选型中的比较研究

J. J. Jamian, Mohd Wazir Mustafa, H. Mokhlis, Mohd Noor Abdullah
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引用次数: 37

摘要

在配电网中安装合适尺寸的分布式发电机(DG),可以最大限度地降低电网的总功率损耗。为了实现这一目标,大多数研究人员使用了多种优化技术来调节DG的输出以计算其最优大小。本文将一种新的秩进化粒子群算法(REPSO)与进化粒子群算法(EPSO)和传统粒子群算法(PSO)进行了比较研究。在粒子群优化(PSO)过程中,REPSO和EPSO都采用了进化规划的概念。在PSO中实现EP可以使整个粒子更快地向最佳值移动。在69母线径向配电系统中确定dg最佳尺寸的试验表明,REPSO优于PSO和EPSO。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Study on Distributed Generator Sizing Using Three Types of Particle Swarm Optimization
Total power losses in a distribution network can be minimized by installing Distributed Generator (DG) with correct size. In line with this objective, most of the researchers have used multiple types of optimization technique to regulate the DG's output to compute its optimal size. In this paper, a comparative studies of a new proposed Rank Evolutionary Particle Swarm Optimization (REPSO) method with Evolutionary Particle Swarm Optimization (EPSO) and Traditional Particle Swarm Optimization (PSO) is conducted. Both REPSO and EPSO are using the concept of Evolutionary Programming (EP) in Particle Swarm Optimization (PSO) process. The implementation of EP in PSO allows the entire particles to move toward the optimal value faster. A test on determining optimum size of DGs in 69 bus radial distribution system reveals the superiority of REPSO over PSO and EPSO.
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