Review of Electric Vehicle Charging Demand Forecasting Based on Multi-Source Data

Electric vehicle (EV) charging demand prediction is an important prerequisite for studying the interaction of EVs with power grids and transportation networks. Since most of the existing work does not use real traffic data to analyze EV charging demand or consider single data in demand analysis, for this reason, this article reviews the related research of EV charging demand prediction, and the charging demand characteristics of different vehicle owner groups is summarized, as well as the current commonly used charging demand analysis models is summarized, including the travel chain model based on user travel, the BASS model of EV ownership prediction, and considering River Closure model of traffic flow. Then, the prediction of EV charging demand that integrates multi-source data information is proposed, such as road network, transportation, power grid, weather, vehicles, charging facilities, including traffic flow data, transportation network data, crowd distribution data, charging station distribution data, and air temperature data.