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Bilevel Programming Approach for Optimal Planning Design of EV Charging Station

机译:EV充电站最优规划设计的双脚编程方法

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This article proposes a new methodological framework to optimize the planning design of an electric vehicle (EV) charging station with renewable energy resources (RCS). Differing from extant studies, the proposed approach explicitly considers the strategic self-interested nature of EV users under a fully liberalized market environment and aims at fully exploiting the flexibility of EV charging loads to enhance the efficiency of renewable energy utilization. Such a problem has been formulated as a bilevel programming model with equilibrium constraints. In this formulation, the upper level problem determines the optimal configuration of the RCS and its operation/pricing schemes simultaneously to maximize the total profits of RCS owner, while the lower level models the strategic charging decisions of EV users in response to the provided pricing scheme of RCS owner. The resulting bilevel optimization model is reformulated into an equivalent single-level linear program, by replacing the lower level problem with Karush–Kuhn–Tucker conditions and linearizing the bilinear products via McCormick relaxation and Big-M technique. The simulation results from case studies demonstrate the effectiveness of the proposed methodology.
机译:本文提出了一种新的方法框架,以优化具有可再生能源资源(RCS)的电动车辆(EV)充电站的规划设计。与现存研究不同,拟议的方法明确考虑了EV用户在一个完全自由化的市场环境下的战略自私性,并旨在充分利用EV充电负荷的灵活性,以提高可再生能源利用效率。这种问题已被制定为具有均衡限制的双纤维编程模型。在该制定中,上层问题同时确定RCS及其操作/定价方案的最佳配置,以最大限度地提高RCS所有者的总利润,而较低级别模拟EV用户的战略充电决策响应于所提供的定价方案RCS所有者。由此产生的BileVel优化模型被重新重新重整为等同的单级线性程序,通过用karush-kuhn-tucker条件替换较低的水平问题,并通过McCormick弛豫和Big-M技术进行线性化。案例研究的仿真结果证明了提出的方法的有效性。

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