Joint Planning of Battery Swapping Stations and Distribution Networks to Enhance Photovoltaic Utilization

High photovoltaic (PV) penetration in distribution networks (DNs) often causes network congestion, which in turn leads to renewable curtailment. Existing studies on battery swapping stations (BSSs) mainly focus on energy management of established stations, rather than system-level planning and coordination. To address these challenges, this study proposes a coordinated planning method for electric vehicle (EV) BSSs to improve PV utilization. The method integrates BSS siting, capacity sizing, and price-subsidy strategies into a unified mixed-integer linear programming (MILP) model. The model is developed to integrate road networks (RNs) and DNs, capturing the interaction between EV battery swapping behavior and DN operation. By guiding swapping behavior through price-subsidy strategies to align with local PV output, the method enables more flexible energy utilization and mitigates network congestion. Case studies are conducted on a combined IEEE 33-bus DN system and Sioux Falls RN. Results show that the proposed method can effectively improve local PV utilization and reduce curtailment without violating DN operational constraints. Overall, the proposed method provides an efficient and practical decision-support tool for the integrated planning of BSSs and renewable-rich DNs.