Research on dynamic forecasting method of electric vehicle charging load in courts

EVs' vigorous development impacts the power grid, so accurately predicting their charging load is urgent. This paper proposes a dynamic forecasting method for large-scale EV charging load based on the Monte Carlo method. It constructs a charging load scenario, considers various influencing factors, combines historical and real-time data to build a prediction model, and captures the load's randomness and uncertainty. The statistical analysis method is used to study different scenarios and optimize the model. Horizontal comparison and verification show the model has small prediction error, high precision, practicability, and popularization value, providing support for power grid optimization and clean energy development.