ENHANCING EV CHARGING PERFORMANCE WITH ANNCONTROLLED HYBRID (SOLAR/WIND) SYSTEMS
Keywords:
ANN Contoller, PI Controller, Buck converter, Boost converter,, Electric vehicle charging station (EV charging station).Abstract
This paper explores the enhancement of electric vehicle (EV) charging performance through the integration of an Artificial
Neural Network (ANN) controller within a solar/wind hybrid power system. The study focuses on designing a robust,
efficient system that makes use of the complementary qualities of wind and sun energy sources to guarantee a steady and
dependable supply of power. By incorporating ANN control strategies, the system dynamically adjusts to fluctuations in
energy production and demand, optimizing the charging process for EVs. The proposed hybrid system not only improves
energy efficiency but also reduces dependency on the conventional grid, promoting sustainable and eco- friendly
transportation solutions. Simulation results demonstrate significant performance gains in terms of energy utilization and
charging speed, highlighting the potential of ANN-controlled hybrid systems in advancing the EV charging infrastructure.
