Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Willy Stephen Tounsi Fokui, L. Ngoo, Michael Juma Saulo
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引用次数: 1

Abstract

This paper proposes a method of optimally utilizing electric vehicles (EVs) in the distribution network. The method is firstly based on segregating the distribution network into communities and then optimally placing an EV charging station (EVCS) in each community using the backward forward sweep (BFS) technique. The Second phase uses particle swarm optimization (PSO) to size and allocates photovoltaic systems in the network for power loss minimization and voltage improvement. The proposed method is tested on an IEEE 33 node test feeder and simulation results showed the effectiveness of the BFS in finding the best nodes for the placement of EVCS in each community as well as the effectiveness of the PSO in allocating the photovoltaic systems. To validate the effectiveness of the BFS technique, its results obtained are compared with those obtained when the EVCSs are placed on some nodes other than those chosen by the BFS technique.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
社区配电网中电动汽车充电站与补偿光伏系统的优化集成
本文提出了配电网中电动汽车的优化利用方法。该方法首先将配电网划分为多个社区,然后采用后向扫描(BFS)技术在每个社区中最优设置电动汽车充电站。第二阶段采用粒子群优化(PSO)对电网中的光伏系统进行尺寸和分配,以实现功率损耗最小化和电压改善。在IEEE 33节点测试馈线上对该方法进行了测试,仿真结果表明BFS在寻找EVCS在每个社区中的最佳节点以及PSO在光伏系统分配方面的有效性。为了验证BFS技术的有效性,将其结果与将evcs放置在非BFS技术选择的节点上的结果进行了比较。这是一篇在知识共享署名许可(http://creativecommons.org/licenses/by/4.0/)条款下发布的开放获取文章,该许可允许在任何媒介上不受限制地使用、分发和复制,只要原始作品被适当引用。
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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