Efficient optimal scheduling of charging station with multiple electric vehicles via V2V

Pengcheng You, Zaiyue Yang
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引用次数: 42

Abstract

This paper investigates the scheduling problem of an intermediary charging station with multiple electric vehicles (EV) in real-time electricity pricing environment. A charging aggregator (CA) is in charge to coordinate EVs' charging so that all EVs' requirements are met and meanwhile the total social cost is minimized. Besides, a new charging mechanism named Vehicle-to-Vehicle (V2V) is proposed to take full advantage of every EV's battery energy. Due to the binary state of EVs, i.e., charging and discharging, scheduling of the charging station is formulated as a constrained mixed-integer linear program (MILP). A distributed algorithm is applied to solve the problem by means of dual decomposition and Benders decomposition. Therefore, scheduling is carried out on each EV and coordinated by the CA. Numerical results show efficiency of the proposed approach and validate our theoretical analysis.
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基于V2V的多电动汽车充电站高效优化调度
研究了实时电价环境下多辆电动汽车的中间充电站调度问题。充电聚合器(charging aggreator, CA)负责协调电动汽车的充电,以满足电动汽车的所有需求,同时使社会总成本最小化。此外,还提出了一种新的充电机制——车对车(V2V),以充分利用每辆电动汽车的电池能量。针对电动汽车充电和放电的二元状态,将充电站的调度表述为约束混合整数线性规划(MILP)。采用对偶分解和Benders分解的分布式算法求解该问题。因此,在每个EV上进行调度并由CA进行协调。数值结果表明了该方法的有效性,验证了理论分析的正确性。
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