An electric vehicle charging station planning model based on charging service capacity and distribution network acceptance constraints

The widespread promotion and adoption of electric vehicles (EVs) require the establishment of a comprehensive and convenient charging infrastructure network. To facilitate the development of the EV market, meet user charging demands, enhance overall societal benefits, and address challenges such as lagging infrastructure development, inadequate charging station networks, and suboptimal site selection, it is crucial to optimize the siting of charging stations. This optimization must balance EV travel requirements and urban power supply capacity while minimizing unnecessary consumption of public resources. To address these challenges, charging capacity is first quantified. The traffic demand prediction model need not only to estimate the traffic flow at the vehicle convergence nodes but also to take into account the necessity of charging to provide an accurate view of actual service capacities in the charging network. Therefore, the charging service within the actual network is modeled based on traffic demand. Next, during simulation, multiple factors are comprehensively considered, including charging power, start and end times of charging sessions, duration of charging, and the state of charge at the beginning of charging. Finally, an EV charging station model is constructed and solved using a genetic algorithm.