Optimized control strategy for enhanced stability in grid-connected photovoltaic-wind hybrid energy systems

Abstract

To improve stability in grid-connected photovoltaic-wind (PV-wind) hybrid energy systems, this research presents optimized model predictive control (MPC) and proportional resonant (PR) control algorithms. The proposed MPC strategy enhances power management by forecasting future system behavior and optimizing control actions accordingly, while the PR controller effectively handles grid-synchronized voltage regulation and harmonic compensation. Together, these advanced control techniques significantly improve grid stability, ensure optimal utilization of renewable energy resources (RER), and maintain power quality under varying operating conditions. The performance of the hybrid system is evaluated through extensive simulations that consider a range of real-world scenarios, including fluctuating load demands and diverse climatic conditions. The results confirm the effectiveness of the proposed MPC and PR-based control in dynamically adjusting power output from wind and photovoltaic sources, thereby ensuring reliable and efficient grid integration. These findings highlight the potential of intelligent control systems in enabling the secure, stable, and long-term adoption of renewable energy within modern power grids.