Vehicle to Grid

Vehicle-to-Grid (V2G) technology harnesses electric vehicles (EVs) as distributed energy resources, enabling bidirectional power flow between EVs and the power grid to improve grid stability and efficiency. Current research emphasizes developing sophisticated control algorithms, often employing reinforcement learning (e.g., Deep Deterministic Policy Gradient, federated learning) and multi-agent systems, to optimize EV charging/discharging schedules while considering diverse objectives like minimizing grid load fluctuations, maximizing renewable energy integration, and ensuring individual driver needs. This research is crucial for facilitating the large-scale integration of EVs into the power grid, enhancing grid resilience, and potentially creating new revenue streams for EV owners and grid operators.