Battery swapping stations (BSSs) present an alternative way of charging electric vehicles (EVs) that can lead toward a sustainable EV ecosystem. Although research focusing on the BSS strategies has been ongoing, the results are fragmented. Currently, an integrated way of considering stochastic EV station visits through planning and operations has not been fully investigated. To create comprehensive and resilient battery swapping stations, a two-stage optimization with recourse is proposed. In the planning stage, the investment for battery purchases is recommended even before the EV station visit uncertainties are made known. In the operation stage, the battery allocation decisions, such as charging, discharging, and swapping are then coordinated. To apply the recourse strategy in creating representative scenarios, the EV station visit distribution techniques are also proposed using a modified K-means clustering method. Aside from the sensitivity analysis made with swapping prices and charging intervals, the strategy comparisons with conventional strategies have also demonstrated the practicality of the BSS coordination to future electricity and transportation networks.

中文翻译：

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考虑电动汽车不确定性的电池交换站优化追索策略

电池交换站 (BSS) 提供了一种为电动汽车 (EV) 充电的替代方式，可以实现可持续的 EV 生态系统。尽管针对 BSS 策略的研究一直在进行，但结果是零散的。目前，尚未充分研究通过规划和运营来考虑随机电动汽车站访问的综合方法。为了创建全面且有弹性的电池更换站，提出了具有追索权的两阶段优化。在规划阶段，甚至在电动汽车站访问的不确定性被告知之前，建议购买电池的投资。在运行阶段，协调充电、放电和交换等电池分配决策。将追索策略应用于创建具有代表性的场景，还提出了使用改进的 K 均值聚类方法的电动汽车站访问分布技术。除了对交换价格和充电间隔进行敏感性分析外，与传统策略的策略比较也证明了 BSS 协调对未来电力和交通网络的实用性。