Stability Enhancement of Island Grids via Model Predictive Control Parameter Optimization

To improve the reliability of power systems, Model Predictive Control (MPC) has emerged as a highly effective approach for optimizing parameters in Battery Energy Storage Systems (BESS) and other components. This study utilized MPC to identify the ideal settings for an island microgrid across two scenarios: one focused solely on optimizing BESS controller parameters, and the other addressing the simultaneous optimization of parameters for the BESS controller, photovoltaic (PVs) units, and wind turbines (WTs). By analyzing system performance under varying conditions, the researchers developed a detailed and accurate perspective on its operational behavior. The MPC algorithm was programmed in Python and integrated with DigSilent PowerFactory for simulation purposes, ensuring practicality for practise applications. Simulations in the time domain showcased the capability of the MPC-driven BESS and Renewable Energy Sources (RES) system to mitigate power system oscillations effectively.