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Nature-Inspired Optimization Algorithms Applied for Solving Charging Station Placement Problem: Overview and Comparison

机译:自然启发优化算法应用于解决充电站放置问题:概述和比较

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The escalated energy demand in conjunction with the global warming and environmental degradation has paved the path of transportation electrification. Electric Vehicles (EVs) need to recharge their batteries after travelling certain distance. Thus, large scale deployment of EVs calls for development of sustainable charging infrastructure. The placement of charging stations is a complex optimization problem involving a number of decision variables, objective functions, and constraints. Placement of charging station mimics a non-convex and non- combinatorial problem involving both transport and distribution network. The complex and non-linear nature of the charging station placement problem has compelled researchers to apply Nature Inspired Optimization (NIO) algorithms for solving the problem. This study aims to review the NIO algorithms applied for solving the charging station placement problem. This work will endow the research community with a systematic review of NIO algorithms for solving charging station placement problem thereby revealing the key features, advantages, and disadvantages of each of these algorithms. Thus, this work will help the researchers in selecting suitable algorithm for solving the charging station placement problem and will serve as a guide for developing efficient algorithms to solve the charging station placement problem.
机译:随着全球变暖和环境退化的升级能源需求铺设了运输电气化的路径。电动汽车(EVS)需要在一定距离后给予电池。因此,大规模部署EVS呼吁开发可持续收费基础设施。充电站的放置是一个复杂的优化问题,涉及许多决策变量,客观函数和约束。充电站的放置模拟了涉及运输和分配网络的非凸面和非组合问题。充电站放置问题的复杂和非线性性质已经推动了研究人员,以应用自然启发优化(NIO)算法来解决问题。本研究旨在审查应用于解决充电站放置问题的NIO算法。这项工作将赋予研究界,并对NIO算法进行系统审查,用于解决充电站放置问题,从而揭示了这些算法中的每一个的关键特征,优点和缺点。因此,这项工作将帮助研究人员选择用于解决充电站放置问题的合适算法,并将用作开发有效算法以解决充电站放置问题的指导。

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