Optimal Location of Electric Vehicles in a Wind Integrated Distribution System Using Reptile Search Algorithm

N. Rehman, M. Mufti, Neeraj Gupta
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引用次数: 2

Abstract

Distributed generation (DG) has been employed over the years in distribution systems to enhance system voltage profile, improve voltage regulation and minimise power losses leading to improved stability besides economic benefits. This work addresses an application of reptile search algorithm (RSA) based optimization technique to determine the optimal placement of electric vehicles (EVs) in distribution systems. A matrix approach based radial distribution load flow method is adopted to determine the optimal location of DGs with the heuristic intelligent search approach of RSA looking after the optimal placement of EV loads. This work presents a standard IEEE-33 and 69 bus system integrated with a wind turbine generating system (WTGS). The system is modeled for optimal placement of EV loads such that the system voltage is maintained within allowable limits by reducing overall system losses. The optimal placement of EV loads in a radial distribution network (RDN) implies establishing an efficient active distribution network satisfying several operating parameters like bus voltage limits and current capacity of feeders while maintaining network radiality with minimal system losses. The proposed technique is investigated on the benchmark IEEE-33 and 69 bus test systems. The simulated results depict a substantial improvement in convergence characteristics and reduction in system losses.
基于爬行动物搜索算法的电动汽车在风力综合配电系统中的最优定位
多年来,分布式发电技术已被应用于配电系统,以改善系统电压分布,改善电压调节和减少电力损耗,从而提高稳定性和经济效益。这项工作解决了基于爬行动物搜索算法(RSA)的优化技术的应用,以确定电动汽车(ev)在配电系统中的最佳位置。采用基于矩阵法的径向分布潮流法确定dg的最优位置,采用RSA启发式智能搜索方法考虑EV负载的最优布局。这项工作提出了一个标准的IEEE-33和69总线系统集成的风力发电系统(WTGS)。该系统为EV负载的最佳放置建模,从而通过减少整体系统损耗将系统电压保持在允许的范围内。在径向配电网(RDN)中,电动汽车负荷的最佳配置要求建立一个有效的有源配电网,在保证电网径向性的同时,满足母线电压限值和馈线电流容量等多个运行参数,并使系统损耗最小。在基准的IEEE-33和69总线测试系统上对该技术进行了研究。仿真结果表明,该方法在收敛特性和减少系统损耗方面有了显著改善。
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