Real-time Charging Scheduling Strategy for Battery Swapping Station Based on GRU
In the battery swapping mode of the electric vehicle(EV),the battery charging strategy of battery swapping station is significant to the swapping operator,distribution network and EV swapping cost.In actual operation,a critical issue is to determine the number and power of batteries to charge and discharge in real-time.This paper proposes a real-time scheduling method based on gate recurrent unit(GRU),which can make charging and discharging decisions online.The battery swapping station charging model is established,and the optimization results are converted into input samples containing historical and predictive information through data preprocessing.GRU is utilized to learn the generated samples and automatically establish mappings from different times and features to charging decisions.By designing the output standardization method,the final output conforms to the physical logic.The trained neural network can be deployed online to solve problems in milliseconds.Simulation results demonstrate that the proposed method can significantly reduce the operating cost and improve the service quality of the battery swapping station.
万方数据
维普
