A Novel Hybrid Approach for Power Quality Improvement in a Vehicle-to-Grid Setup Using Droop-ANN Model

The integration of electric vehicles (EVs) in the power grid has attracted considerable attention due to its potential benefits, such as demand response and quality improvement. However, intermittent unpredictable nature EVs’ charging discharging behavior can cause significant challenges grid’s stability quality. This research study explores use a droop-ANN model improve vehicle-to-grid (V2G) systems. proposed approach integrates an artificial neural network (ANN) into droop control technique accurately predict voltage frequency charger. Through simulations, model’s effectiveness reducing fluctuations enhancing was validated. results indicate that significantly improves across various battery state charge (SoC) charging/discharging scenarios. findings highlight enhance reliability V2G Further is needed validate real-world applications explore full potential. Overall, offers promising solution for improving