电网技术2025，Vol.49Issue(2)：470-480,中插24-中插27,15.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
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.关键词
配电网/韧性/换电站/电动汽车换电需求/随机-鲁棒优化/列生成算法Key words
distribution system/resilience/battery swapping station/EV battery swapping demand/stochastic-robust optimization/column-and-constraint generation algorithm分类
信息技术与安全科学引用本文复制引用
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,中插24-中插27,15.基金项目
国家重点研发计划项目(2022YFB2603100) （2022YFB2603100）
四川省科技计划项目(2023YFG0107) （2023YFG0107）
中央高校基本科研业务费专项资金项目(2682024CX033).Project Supported by the National Key Research & Development Program of China(No.2022YFB2603100) （2682024CX033）
Sichuan Science and Technology Program(No.2023YFG0107) （No.2023YFG0107）
the Fundamental Research Funds for the Central Universities(No.2682024CX033). （No.2682024CX033）
