Multi-Layer Perceptron-Recurrent Neural Network VSC for EV Charging Stations with Integrated Renewable Energy Systems

The application of Multilayer Perception-Recurrent Neural Network (MRNN) based vector control for Voltage Source Converters (VSC) in EV charging stations integrated with photovoltaic (PV), wind, and battery storage systems is thoroughly examined in this article. Improving power quality by reducing harmonics and making sure that, even with nonlinear loads and changing irradiance, the grid current's Total Harmonic Distortion (THD) stays within IEEE standards are the key goals. In order to maintain stable PV system operation and efficient battery charging and discharging in both grid-connected and islanding modes, the article also focuses on dependable energy management by controlling the DC link voltage via the battery's bidirectional converter. For the dc-dc converter of the EV charging station, a model predictive direct current control (MPC) is suggested. The system's capacity to maintain system stability in real-world situations and function well in dynamic conditions like fluctuating wind and irradiance is thoroughly assessed. Two lines are used to elaborate on the same words.