AI‐Enhanced Reactive Power Compensation in Weak Grids Integrating Wind Energy Systems

Voltage stability and reactive power changes provide issues for wind energy systems that enhance a weak grid. The problem of improving reactive power compensation in weak grid conditions using wind energy systems is discussed in this research in a practical and risk-aware approach. The system employs artificial intelligence (AI) techniques to study reactive power requirements in light of variability in the grid and wind energy output. Through the application of machine learning algorithms to predictive models, the system dynamically identifies and corrects grid modifications to minimize voltage instability and secure grid results. Through risk management practices the proposed approach provides substantial reliability value by evaluating the reliability of configured models and creating sound decision processes. The presented solution provides a practical power system design for high renewable energy applications because it improves grid performance and reduces voltage fluctuations and enhances wind energy integration when grids experience weakness.