Impact of Optimum Allocation of Distributed Generations on Distribution Networks Based on Multi-Objective Different Optimization Techniques

A. Saleh, A. Mohamed, A. Hemeida
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引用次数: 7

Abstract

A number of different optimization algorithms namely, Moth Swarm Algorithm (MSA), and Particle Swarm Optimization (PSO) algorithm are presented and compared in this paper. Different optimization techniques are used to determine the optimum allocation of distributed generation (DG) in radial distribution systems during reduction of single and multi-objective function namely, (total network power losses, voltage deviation, and total operating cost). The multi objective function is formed by using the weighted sum method. In this paper, multiple-DG units have been analyzed under two load power factors (i.e., unity and optimal). The proposed algorithms have been tested on the 33-bus radial distribution network. The performance of the different optimization algorithms has been compared with other evolutionary optimization technique under different system operating conditions. The simulation results observed the impact of integrating the proper size of DG at the suitable placement based on different techniques.
基于多目标差分优化技术的配电代优化分配对配电网的影响
本文介绍了几种不同的优化算法,即飞蛾群算法(MSA)和粒子群算法(PSO),并进行了比较。采用不同的优化技术来确定径向配电系统中分布式发电的最佳配置,同时降低单目标和多目标函数(即网络总损耗、电压偏差和总运行成本)。采用加权和法形成多目标函数。本文对多台dg机组在统一和最优两种负载功率因数下进行了分析。所提出的算法已在33总线径向配电网上进行了测试。在不同的系统运行条件下,比较了不同优化算法与其他进化优化技术的性能。仿真结果观察了基于不同技术在合适位置积分DG尺寸的影响。
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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