ELECTRIC VEHICLE CHARGING INFRASTRUCTURE WITH INTEGRATED DISTRIBUTED ENERGY RESOURCES

Abstract

The increasing demand for electric vehicles (EVs) requires the development of efficient and flexible EV charging stations that can seamlessly integrate with the electric grid. This paper presents a distributed energy resource (DER)-based EV charging station that leverages renewable energy sources such as solar and wind, along with battery storage systems. The proposed system ensures a seamless connection to the grid, allowing for bidirectional power flow, grid support, and energy optimization. An Artificial Neural Network (ANN) controller is utilized to optimize the power management strategy of the charging station. The ANN-based controller enables realtime adaptive control, balancing the power flow between the DERs, energy storage, and the grid to meet the dynamic demand of the EVs while maintaining grid stability. The controller ensures voltage regulation, current control, and minimization of power losses, thereby enhancing the overall efficiency and performance of the system. It also enables the charging station to supply power back to the grid in case of excess energy. Simulation and experimental results demonstrate the effectiveness of the proposed system in terms of improved energy efficiency, reduced charging time, and stable integration with the grid. This approach presents a promising solution for the development of sustainable EV charging infrastructure, supporting smart grid technologies and renewable energy integration