Energy Management through V2G concept with EV Charging/Discharging Strategy

Abstract

The integration of Vehicle-to-Grid (V2G) technology has emerged as a promising solution for managing energy demand, enhancing grid stability, and reducing peak loads. This paper explores an advanced V2G-based energy management system that incorporates renewable energy sources (RES), such as solar and wind, to further optimize grid operations. By leveraging bidirectional energy flow between EVs and the grid, combined with real-time forecasting of RES generation, the system addresses renewable intermittency and maximizes energy utilization. A novel algorithm is developed to schedule the charging and discharging of electric vehicles (EVs) based on load demand profiles, EV parking plans, and RES availability. The proposed approach ensures that EVs charge during peak RES generation periods and discharge energy back to the grid during high demand hours, contributing to peak load shaving. A case study is conducted for Gujarat, India, demonstrating the effectiveness of the proposed system in reducing grid stress, improving load profiles, and supporting clean energy integration. The results reveal significant reductions in peak loads and enhanced grid reliability, making this approach a sustainable solution for smart energy management. Future work will explore machine learning-based predictive models to further refine energy scheduling and optimize real-time grid support.