Optimization of Charging Station Deployment Based on Travel Chain Charging Load Prediction

The increasing demand for electric vehicles has led to concerns about charging infrastructure. This study proposes an optimization framework for deploying charging stations based on travel chain charging load prediction. First, the theory of travel chains is applied to characterize the behavior of electric vehicle (EV) users, which serves as the basis for the developed predictive model that assesses charging loads in terms of both location and time. This model is then evaluated through Monte Carlo simulations to determine charging demands. Subsequently, to reduce the overall societal costs, an optimization method is applied for the arrangement of charging stations, considering their types, quantities, and locations. The results of this study provide valuable insights into optimizing charging station deployment strategies that can help balance the benefits among multiple entities involved in EV charging infrastructure planning.