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Joint Planning of EV Fast Charging Stations and Power Distribution Systems With Balanced Traffic Flow Assignment

机译:具有平衡交通流量分配的EV快速充电站和配电系统的联合规划

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To tackle the challenges introduced by the fast-growing charging demand of electric vehicles (EVs), the power distribution systems (PDSs) and fast charging stations (FCSs) of EVs should be planned and operated in a more coordinated fashion. However, existing planning approaches generally aim to minimize investment costs in PDSs while ignoring the risk of worsening traffic conditions. To overcome this research gap, this article integrates the interests of traffic networks into PDS and FCS joint planning model to mitigate negative impacts on traffic conditions caused by installing FCSs. First, a novel microscopic method that is different from traditional assignment methods is proposed to simulate the influences of FCSs on traffic flows and EV charging loads. Then, a multiobjective joint planning model is developed to minimize both the planning costs and unbalanced traffic flows. A new bilayer Benders decomposition algorithm is designed to solve the proposed joint planning model. Numerical results on two practical systems in China validate the feasibility of our microscopic method by comparing the simulated results with real data. Compared with existing approaches, it is also demonstrated that the proposed joint planning approach helps to balance traffic flow assignments and relieve traffic congestion.
机译:为了解决电动车辆(EVS)的快速增长充电需求所引入的挑战,应该以更协调的方式计划和操作EVS的配电系统(PDS)和快速充电站(FCS)。然而,现有的规划方法通常旨在最大限度地降低PDS中的投资成本,同时忽略交通状况恶化的风险。为了克服这一研究缺口,本文将交通网络的利益与PDS和FCS联合规划模型集成,以减轻对安装FCSS引起的交通状况的负面影响。首先,提出了一种与传统分配方法不同的微观方法,以模拟FCSS对交通流量和EV充电负荷的影响。然后,开发了一种多目标联合规划模型以最大限度地减少规划成本和不平衡的交通流量。新的双层弯曲器分解算法旨在解决所提出的联合规划模型。在中国的两个实际系统上的数值结果通过比较与实际数据的模拟结果进行比较来验证我们的微观方法的可行性。与现有方法相比,还表明,拟议的联合规划方法有助于平衡交通流动分配并减轻交通拥堵。

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