Fault Ride-Through Capability of EV Charging Station using ANN and ANFIS Controllers

Electric vehicles and their charging infrastructures have seen rapid development in the recent past. With that advancement, the need for consistent and efficient grid-integrated charging stations has become inevitable. This research contributes to developing an efficient and reliable control strategy for electric vehicle charging stations, promoting the integration of charging infrastructure into the power grid while maintaining the stability of the charging system under voltage instabilities. A fault ride-through capability of charging stations in handling sudden voltage changes, especially during critical situations, is presented in this work. The study focuses on integrating an artificial neural network-based controller (ANN) and adaptive neuro-fuzzy interference system (ANFIS) for the DVR of the charging station. The performance of this proposed controllers are compared with a simple PID controller on the same charging station during critical voltage conditions. Under various conditions, the proposed controllers can effectively regulate the charging process and maintain the voltage stability of the charging system. MatLab simulation results indicate that the proposed ANN controller comparatively enhance the charging station’s ability to handle challenges due to the quality of supply, improve faults right through the capability of the DVR associated with the charging system, and maintain smooth operation even when voltage quality changes unexpectedly.