Optimal Placement of Distributed Energy Resources Including Different Load Models Using Different Optimization Techniques

A. Mohamed, S. M. Ali, A. Hemeida, A. A. Ibrahim
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引用次数: 11

Abstract

This article introduces how to improve the real power losses and voltage deviation in distributed network system due to Distributed Energy Resources (DERs) allocation strategy by using Moth Swarm Algorithm (MSA) and Differential Evolution (DE) Algorithm. The proposed Optimization techniques are implemented on 33-bus and 69-bus IEEE standard radial distribution test systems with constant, industrial, residential, and commercial loads. The evaluated results have been confirmed the superiority with high performance of the DE technique than MSA technique to find the best solutions of DERs units allocation for different load factors.
采用不同优化技术的不同负荷模型分布式能源优化配置
本文介绍了如何利用飞蛾群算法(MSA)和差分进化算法(DE)改善分布式电网系统中由于分布式能源分配策略而产生的实际功率损耗和电压偏差。所提出的优化技术在33总线和69总线的IEEE标准径向配电测试系统中实现了恒定负载,工业,住宅和商业负载。评价结果表明,相对于MSA技术,DE技术在寻找不同负荷因素下der单元分配的最佳解方面具有高性能的优越性。
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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