郭毅娜, 廖凯, 杨健维, 何正友. 兼顾配电网韧性提升的电动汽车换电站容量优化配置方法[J]. 电网技术, 2025, 49(2): 470-480. DOI: 10.13335/j.1000-3673.pst.2024.0677
引用本文: 郭毅娜, 廖凯, 杨健维, 何正友. 兼顾配电网韧性提升的电动汽车换电站容量优化配置方法[J]. 电网技术, 2025, 49(2): 470-480. DOI: 10.13335/j.1000-3673.pst.2024.0677
GUO Yina, LIAO Kai, YANG Jianwei, HE Zhengyou. Optimal Capacity Allocation Method of Battery Swapping Station Considering Distribution System Resilience Enhancement[J]. Power System Technology, 2025, 49(2): 470-480. DOI: 10.13335/j.1000-3673.pst.2024.0677
Citation: GUO Yina, LIAO Kai, YANG Jianwei, HE Zhengyou. Optimal Capacity Allocation Method of Battery Swapping Station Considering Distribution System Resilience Enhancement[J]. Power System Technology, 2025, 49(2): 470-480. DOI: 10.13335/j.1000-3673.pst.2024.0677

兼顾配电网韧性提升的电动汽车换电站容量优化配置方法

Optimal Capacity Allocation Method of Battery Swapping Station Considering Distribution System Resilience Enhancement

  • 摘要: 电动汽车换电站(battery swapping stations,BSS)因具有丰富电池资源和便于集中调度的优势,为配电网韧性提升提供了新的解决思路。合理的容量配置,可促使BSS在配电网韧性提升方面发挥更为重要的作用。为此,提出一种兼顾配电网韧性提升的BSS容量优化配置方法。通过构建电动汽车换电需求和供电能力影响下的BSS容量配置限值约束,保证BSS交通属性的同时,提升BSS有效支撑配电网供电恢复的能力。在此基础上,计及配电网故障场景不确定性和新能源出力不确定性,以最小化BSS投资运维成本和配电网失负荷之和为目标,建立BSS两阶段随机-鲁棒优化配置模型,以实现BSS容量最优配置。针对所建模型特点,采用双层列生成算法对所建模型进行求解,并通过算例仿真对所提BSS容量配置方法的合理性和有效性进行验证。结果表明,所提BSS容量配置方法能够在尽可能降低BSS建设成本的前提下有效提升配电网韧性。

     

    Abstract: Battery swapping stations (BSS) offer a novel solution for DS resilience enhancement with their abundant battery resources and ease of centralized dispatch. With proper capacity allocation, BSS could play a more crucial role in improving the resilience of the distribution system (DS). Therefore, this paper proposed an optimal capacity allocation method for BSSs to enhance DS resilience. The BSS capacity allocation limit constraint under the influence of electric vehicle (EV) battery swapping demand and BSS power supply capability was formed, which could ensure that BSS can effectively support power grid recovery without compromising traffic attributes. Furthermore, a stochastic-robust capacity allocation model for BSS was developed to achieve optimal capacity allocation, aiming at minimizing the sum of the BSS investment costs and the DS load shedding costs and considering the uncertainties of renewables output and the DS fault scenarios. Based on the characteristics of the established model, the two-level column-and-constraint generation algorithm (C&CG) was adopted for the model solution. The rationality and effectiveness of the proposed method were verified based on a modified IEEE 33-bus distribution system and a 29-node transportation system. The case study shows that the proposed method could effectively enhance DS resilience while reducing the construction cost of BSS.

     

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