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Optimal Placement of Electric Vehicle Charging Stations in a Distribution Network

机译:配电网中电动汽车充电站的优化布置

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The rising popularity and improved environmental awareness are making the present transportation network move towards electric vehicles (EVs). With the increased number of grid-connected EVs, inappropriate placement of charging stations (CSs) will be injurious to city traffic layout and the power distribution network. It will also deprive the convenience of EV owners and increase distribution loss. Therefore, this paper proposes a new method for optimal allocation of CSs by minimizing distribution losses of the system and increasing the utilization factor of CSs. Since these two objectives are contradictory, non-dominated sorting genetic algorithm (NSGAII) is used to solve them. A probabilistic load modelling method is employed to develop the charging demand of EVs. The proposed method is tested on a test system which is obtained by modifying the standard IEEE 33 bus system. Simulation results show that the proposed method is not only able to reduce the system loss but also achieve economical benefits while placing CSs in a network.
机译:日益普及的环境和提高的环保意识正在使当前的交通网络向电动汽车(EV)转移。随着并网电动汽车数量的增加,充电站(CS)的不当放置将危害城市交通布局和配电网络。这也将剥夺电动车车主的便利,并增加分销损失。因此,本文提出了一种通过最小化系统的分配损失并增加CS的利用率来优化CS分配的新方法。由于这两个目标是矛盾的,因此使用非支配排序遗传算法(NSGAII)来解决它们。采用概率负荷建模方法来开发电动汽车的充电需求。所提出的方法在通过修改标准IEEE 33总线系统而获得的测试系统上进行测试。仿真结果表明,该方法不仅可以减少系统损耗,而且在将CS放置在网络中时也能获得经济效益。

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