Short-Term Load Forecast of Electric Vehicle Charging Station Based on SE-ALSTM-CNN

With the rapid growth of electric vehicles (EV) over the past few years, accurate short-term load forecast of EV charging stations plays a critical role to reduce the impact of charging load on the power grid. To improve the forecasting accuracy, this paper proposes a short-term charging load forecasting method for the EV charging stations based on ALSTM-SE-CNN neural network. The experimental analysis and model comparison based on real EV charging station load data and relevant auxiliary forecasting data validates the effectiveness and superiority of the proposed method and provide a reliable basis for the optimal scheduling and energy management of charging stations and power grids.