Optimizing Charging and Discharging at Bus Battery Swap Stations Under Varying Environmental Temperatures

The grid ancillary service capability of bus swapping stations (BSSs) is significantly affected by environmental temperature fluctuations and the disorderly charging and discharging of batteries. This study addressed these challenges by developing a comprehensive optimization model for scheduling BSS operations under varying environmental conditions. First, based on real-world energy consumption and temperature data, an energy consumption coefficient correction method was proposed to improve the accuracy of energy consumption calculations. Next, a greedy strategy was utilized to match vehicle battery swapping demands with available batteries in the BSS. A two-layer multi-objective optimization model was then constructed to optimize the charging and discharging power. The upper layer minimizes the total costs, including charging/discharging costs and battery degradation costs, while the lower layer minimizes the load peak-valley difference and maximizes the charging/discharging balance among all batteries. Numerical simulations of the proposed energy consumption correction coefficient improved the accuracy of electric bus energy consumption estimation. Additionally, the proposed optimization strategy reduced the operational cost of the bus battery swapping station by 53.09% and decreased the transformer’s maximum load rate by 28.28%.