Abstract:Charging station operation system provides charging service for electric vehicles, and connects with power grid, charging station, power network and traffic network data center. It achieves efficient operation and management of charging station through information sharing, interaction and data mining of database. In this paper, the overall structure and data analysis of the operation system of intelligent charging station are discussed. Using Q-Learning algorithm to analyze user charging decision from the point of view of realizing the optimum (small) total cost and making the optimum charging service selection can predict user charging behavior rule in operation data mining, and then predict the utilization status of operating charging station equipment, which can charge under different charging facility planning schemes. Load calculation is more real and accurate, so as to obtain more accurate operation cost of charging station, and ultimately provide basis for charging service operation strategy formulated by charging station, and then help charging station to improve equipment utilization and operational efficiency of charging station. It also provides decision-making basis for future expansion and new charging station equipment quantity, type, location and other information.