The Study of Opttimizing Profit for Solar-Energy Integrated Battery Swapping Stations

In response to growing environmental concerns, the widespread adoption of Electric Vehicles (EVs) is imperative, particularly given the transportation sector's significant reliance on fossil fuels. However, successful integration of EVs necessitates an efficient charging and swapping infrastructure to mitigate long charging times and alleviate range anxiety. Battery swapping stations offer a solution akin to traditional gasoline refilling stations by enabling the swift exchange of depleted batteries for charged ones. Beyond customer convenience, this infrastructure also benefits the power system by bolstering grid stability during peak load conditions through battery-to-grid (B2G) functionality. Moreover, batteries can be charged during off-peak periods through grid-to-battery (G2B) mode, leveraging Day-ahead pricing and incorporating solar energy to optimize operations. To address these complexities, we present an optimization model designed to schedule battery charging and discharging based on Day-ahead market prices, integrating considerations such as solar energy availability, battery degradation costs, and customer incentives. This model aims to maximize profits for Battery Swapping Stations (BSS), enhance grid stability, and ensure customer satisfaction. The model is verified in Matlab using Gurobi solver in Yalmip optimizer.