Abstract
Amid escalating concerns over global warming and climate shifts, the imperative for advanced transportation solutions intensifies, aiming to balance economic growth and environmental preservation. The worldwide upsurge in electric vehicle (EV) adoption reflects this transformative aspiration, yet relying solely on fossil fuel-based EV charging infrastructure falls short of addressing climate challenges. In response, Multi Energy Integrated EV Charging Stations have emerged as a pragmatic solution, seamlessly blending renewable energy sources, grid power, and EV charging needs. This study proposes a meticulously crafted charging station design employing Adaptive Neuro-Fuzzy Inference System (ANFIS) technology for voltage-controlled Maximum Power Point Tracking (MPPT), coupled with Type 3 & 2 controllers, which collaborate in harmonious precision to streamline EV charging dynamics and Neural Network-based grid management. The design is meticulously assessed and evaluated using MATLAB/Simulink, presenting a promising avenue for sustainable and efficient EV charging infrastructure in the face of evolving energy demands and environmental concerns.
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