Design of Detection and Assessment System for Electric Vehicle Charging Station Based on Genetic Algorithm

With the large-scale electric vehicle (EV) charging load connected to the power grid, EV charging stations have been widely used. Basic charging facilities are supporting facilities to ensure the convenience of EV travel and affect the growth of EV industry. When building a charging station, several performance indexes with different dimensions should be considered when selecting a charging station. At present, a large quantity of EV charging stations have been built and operated all over the country, and most of them are unattended. In order to maintain the normal operation and use of the charging station, great attention should be paid to the detection and operation maintenance. In this article, aiming at the abnormal state in the detection of DC charging station, the phenomenon and reasons are analyzed, and the detection and assessment model of EV charging station based on genetic algorithm optimized neural network (GANN) is proposed, and the operation state of charging station is analyzed to complete the fault diagnosis. The simulation results show that the assessment model is highly robust and the assessment results are more objective, so that the operation and maintenance strategy of charging stations can be put forward, the performance and safety problems of charging equipment can be solved, and the sustainable growth of EV industry can be promoted.