Intelligent Grid-Connected EV System with Solar PV and Battery for Energy Optimization

Globally, environmentally acceptable refuelling stations are necessary for modern electrical transportation networks. Researchers are at present looking for a practical, ideal solution for EV charging stations because of this. Environmental issues get worse by the switch to electric vehicles (EVs), which are powered by grid electricity derived from the burning of natural resources. Future EVs are entirely environmentally benign modes of transportation because of sustainable charging powered by sustainable energy sources. Hence this work proposes an intelligent grid-connected EV system with solar PV and battery for energy optimization, ensuring reliable energy flow and quality control. A renewable energy system integrating a solar PV array with an EV battery through a bi-directional buck-boost converter. The system employs a Landsman converter for optimizing the power generated from the PV array. A Radial Basis Function Neural Network (RBFNN) based Maximum Power Point Tracking (MPPT) is employed for maximizing energy harvest from the PV module. Moreover, the bi-directional buck-boost converter’s current and voltage is regulated with the aid of Artificial Neural Networks (ANN) controller allows for real-time adjustments to operational parameters. Finally, MATLAB Simulink is used to validate the proficiency of the proposed work. With minimized Total Harmonic Distortion (THD) of 1.75%, demonstrates its effectiveness in reducing harmonic distortion while maintaining reliable performance.