Abstract
Battery Swapping Stations (BSS) offer a faster alternative to conventional EV charging, by replacing depleted batteries with fully charged ones. This decoupling of charging and discharging phases significantly reduces waiting times. However, managing these operations, especially when integrated with renewable energy sources like solar power, requires complex optimization. This paper presents a novel mixed-integer linear programming algorithm to optimize the operations of a BSS integrated with a photovoltaic power plant. The algorithm simulates yearly operations, considering hourly energy prices and grid constraints. It aims to maximize station revenue by optimally scheduling battery charging after swaps and utilizing renewable energy. Simulation results demonstrate significant economic savings, highlighting the algorithm's effectiveness in capitalizing on cost differentials in electricity pricing. This approach provides valuable insights for enhancing the economic viability and operational efficiency of BSS integrated with renewable energy sources.