Using Model Predictive Control in Renewable Energy Sources

The integration of renewable energy sources (RES) poses challenges due to their intermittent nature and the requirement for grid stability and reliability. This study explores the application of Model Predictive Control (MPC) as an advanced control strategy for effective RES integration. MPC utilizes mathematical models and prediction algorithms to optimize power flow, manage system dynamics, and mitigate the intermittent nature of RES. Simulations conducted using Simulink and MATLAB platforms demonstrate the effectiveness of the MPC controller in improving grid stability, optimizing power generation, and accommodating fluctuating RES output. The results highlight the potential of MPC to enhance the integration of RES into the power grid, paving the way for a sustainable and resilient energy infrastructure. Additionally, a comparison between the MPC controller and the Proportional Integral (PI) controller was performed, indicating that MPC outperforms the PI controller.