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The demand for power exchange has risen dramatically as the number of electric vehicle (EV) users has increased, and large-scale disorderly charging will increase the operating costs of battery swapping stations and increase the risk to the power grid. Through experimental comparison with other algorithms on 23 test functions, the results demonstrate that the convergence accuracy and speed of this improved algorithm are superior to those of other algorithms. Furthermore, in solving the optimization problem of EV battery swapping station scheduling, by reasonably allocating the battery pack charging time and establishing the forecasting model of switching demand, the average variance and peak-to-average ratio of the grid are reduced by 29.55% and 13.2%, respectively, based on meeting the user’s switching demand. Approximately a 12,500 RMB reduction in the cost of charging lowers the operation cost and risk of battery swapping stations and enhances the user experience.

Application of Improved Sparrow Search Algorithm in Electric Battery Swapping Station Switching Dispatching