A Charging Station Pricing Model Based on Distribution Network Capacity and Traffic Dynamics

With the widespread adoption of new energy vehicles (EVs), the charging load of electric vehicles significantly impacts the running of distribution networks and the planning of charging infrastructure. To address the challenges of high power losses and inaccurate pricing in existing charging station pricing methods, this paper proposes a pricing method and system for charging stations considering the largest carrying capacity of the distribution network. The method begins by constructing a dynamic urban traffic network model based on actual urban traffic conditions and simulating traffic information. A vehicle model for electric vehicles is then developed to analyze vehicle types, travel times, and battery capacities. Using the OD matrix and Dijkstra algorithm, a path planning model is built to determine the spatiotemporal distribution of charging loads. Finally, a dynamic evaluation of energy value is conducted with the goal of maximizing the load of carrying capacity of the distribution network, optimizing pricing strategies. This method enhances the capacity of the distribution network, improves the efficiency of charging station pricing, and provides theoretical support and practical guidance for charging management and infrastructure development.