The Optimization Strategy for Battery Swapping Stations Charging Scheduling Considering Time-of-Use Electricity Pricing

Battery swapping stations (BSSs) are essential facilities for energy replenishment of electric vehicles (EVs). This paper takes NIO's BSSs as the research subject and, from the perspective of station operators, proposes an optimized battery charging scheduling strategy based on mixed-integer linear programming (MILP), considering the station's service capacity. A charging scheduling optimization model responsive to time-of-use (TOU) electricity pricing is constructed, to minimize the station's charging costs. The model adopts an intermittent charging approach, enabling flexible adjustment of battery charging power and timing according to time-of-use electricity prices, thus dynamically adapting to price fluctuations. Finally, a comparative analysis of typical daily scenarios under different conditions demonstrates that, compared to the traditional continuous charging method, the proposed model optimizes battery charging power distribution, effectively reduces charging costs, alleviates grid load pressure, and achieves peak-load shifting.