A Neural-Guided Three-Phase Photovoltaic Charging Framework for the Elevation of Power Quality in Modern Electromotive Infrastructures

This report presents a better design of an electromotive charging station where a single stage photovoltaic array will be in smooth connection with a three-phase grid via Artificial Neural Network (ANN)-based supervisory control. The proposed system will enhance the quality of power and permit the two-way energy flow between the car and the utility supply. The ANN controller is trained under different operating conditions and thus, the active and reactive power are managed with greater accuracy, resulting in minimised harmonic distortion, voltage stabilisation, and ease of change between grid-connected and islanded operation. The system is higher performance and less structural complexity by removing the requirement of supplemental boost converters and an ingenious estimation of in-phase and quadrature templates. The results indicate that the ANN control improves the tuning challenges, keeps the DC-link stable as well as achieves significant improvements in the event of disturbance, thereby making the charging station more resilient and able to fit the contemporary renewable-infested networks.