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

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.