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Optimal Scheduling of Battery Charging Station Serving Electric Vehicles Based on Battery Swapping

机译:基于电池交换的电动汽车电池充电站优化调度

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A battery charging station (BCS) is a charging facility that supplies electric energy for recharging electric vehicles' depleted batteries (DBs). A BCS has a certain number of charging bays and maintains a dynamic inventory of fully charged batteries (FBs). This paper studies a BCS scheduling (BCSS) problem whose target is to schedule the charging processes of the charging bays such that the charging cost is minimized while satisfying the FB demand. Specifically, the BCSS problem has two types of operations: 1) loading DBs into the charging bays and then unloading them to the FB inventory when they are fully charged and 2) controlling the charging rate of each charging bay. We formulate the BCSS problem as a mixed-integer program with quadratic battery degradation cost. A generalized benders decomposition algorithm is then developed to solve the problem efficiently. The salience of the developed algorithm is that: 1) each charging bay can solve its own subproblem separately and 2) each subproblem can be further partitioned into multiple independent and identically structured quadratic programming problems, and thus the algorithm facilitates an efficient parallel implementation. We perform extensive real data simulation to validate the optimization model and demonstrate the efficiency of the proposed algorithm.
机译:电池充电站(BCS)是为电动汽车的耗尽电池(DB)充电提供电能的充电设施。 BCS具有一定数量的充电槽,并保持充满电的电池(FB)的动态库存。本文研究了一个BCS调度(BCSS)问题,其目标是调度充电站的充电过程,从而在满足FB需求的同时最大程度地降低充电成本。具体来说,BCSS问题有两种类型的操作:1)将DB装入充电槽,然后在它们充满电后再将它们卸载到FB库存中; 2)控制每个充电槽的充电速率。我们将BCSS问题表述为具有二次电池退化成本的混合整数程序。然后,开发了一种通用的Benders分解算法来有效地解决该问题。改进算法的显着性在于:1)每个充电区可以分别解决其自身的子问题; 2)每个子问题可以进一步划分为多个独立且结构相同的二次编程问题,因此该算法有助于有效的并行实现。我们进行了广泛的真实数据仿真,以验证优化模型并证明所提出算法的效率。

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