Smart Vehicle to Grid Energy Management Algorithm for Electric Vehicle Supported by Photovoltaic Energy Sources

Abstract

The paper demonstrates grid improvements with results considering the integration of smart charging algorithms of electric vehicles (EVs) and photovoltaic (PV) energy sources to effectively manage energy flow. It aims to minimize energy costs by leveraging the bidirectional energy transfer capability of EVs and optimizing their interaction with the grid and PV sources. The proposed algorithm takes into account various parameters such as transformer load ratios, solar power generation, and the state of charge of vehicle batteries. The algorithms are implemented by acquiring one year’s real-time data of a predetermined transformer in a neighborhood from the electricity distribution company. The number of EV is estimated for the years 2025 and 2030. Buildings with energy management systems (BEMS), which charge EV with a controlled charging algorithm, provide renewable energy support with PV and reduce the transformer load during peak hours with the V2G algorithm. BEMS is not applied in buildings without EV or PV. Simulation results demonstrate that as the number of EVs increases, renewable energy source support and controlled charging algorithm alone are not sufficient. However, it demonstrate that energy costs and grid stress are successfully minimized by using the V2G algorithm in addition to controlled charging algorithm and PV.