Neural Network-Based PV Powered Electric Vehicle Charging Station

Abstract

Global warming and some dangerous climate changes are becoming more prevalent as the demand for modern transportation systems grows for economic development and cultural comfort. To tackle this global warming issue due to transportation every country pushing for Electric Vehicles (EVs), As the number of electric vehicles on the road rises, Charging EVs with a fossil fuel-based infrastructure alone is not cost-effective or efficient. As a result, a charging station based on renewable energy has enormous potential and control for electric vehicle charging. In the current scenario, a solar-powered electric vehicle charging station and a Battery Energy Storage System (BESS) are required. Additional grid assistance is recommended to ensure that the charging station has uninterrupted power without putting additional burden on the grid, For effective power management in the charging station between solar, BESS, grid, and EVs an efficient charging station design with Adaptive Neuro-Fuzzy Inference System (ANFIS) voltage-controlled MPPT, PID controller, Grid with Neural Network technique is designed and evaluated in MATLAB/Simulink.