Battery swapping–charging system (BSCS) is efficient for battery swapping service provision to commercial electric vehicles (EVs) in a certain region. When multiple BSCSs are considered to serve a larger geographical span, achieving the efficient and collaborative management of the BSCSs located in different regions with various EV user behavior and system features is essential. This article proposed a closed-loop supply chain network-based multiregion battery swapping–charging network (MBSCN) model and a battery logistics model based on a multilayer time–space network technique. A distributionally robust chance-constrained service model is proposed to address the EV uncertainties without requiring assumptions on the probability distributions or a large number of historical data. The battery charging and discharging tasks are optimally allocated to each BSCS according to the locational energy price and the battery demands, while the battery logistics are optimally managed to ensure high-quality battery swapping service provision by considering regional battery demand uncertainties. The optimization problem is formulated as a mixed-integer quadratically constrained programming model and is verified by two case studies. The results indicate that the MBSCN model is more flexible and efficient when interregional battery exchanges are incorporated.

中文翻译：

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电动化公共交通系统多区域换电网络运行管理

电池交换充电系统（BSCS）可有效地为特定地区的商用电动汽车（EV）提供电池交换服务。当考虑多个 BSCS 服务于更大的地理跨度时，实现对位于不同区域、具有各种 EV 用户行为和系统特征的 BSCS 的高效协同管理至关重要。本文提出了基于闭环供应链网络的多区域电池交换充电网络（MBSCN）模型和基于多层时空网络技术的电池物流模型。提出了一种分布鲁棒的机会约束服务模型来解决电动汽车的不确定性，而无需对概率分布或大量历史数据进行假设。根据区域能源价格和电池需求优化分配给每个BSCS的电池充放电任务，同时考虑区域电池需求的不确定性，优化管理电池物流，确保提供高质量的电池更换服务。优化问题被表述为混合整数二次约束规划模型，并通过两个案例研究进行验证。结果表明，当纳入跨区域电池交换时，MBSCN 模型更加灵活和高效。优化问题被表述为混合整数二次约束规划模型，并通过两个案例研究进行验证。结果表明，当纳入跨区域电池交换时，MBSCN 模型更加灵活和高效。优化问题被表述为混合整数二次约束规划模型，并通过两个案例研究进行验证。结果表明，当纳入跨区域电池交换时，MBSCN 模型更加灵活和高效。