A Comparative Study on Weighting Factor Design Techniques for the Model Predictive Control of Power Electronics and Energy Conversion Systems

Abstract

During the past decade, the model predictive control (MPC) of power electronics and drives has witnessed significant advancements in both dynamic performance and range of applications. However, researchers still encounter challenges with the optimal design of weighting factors, and this lowers the capabilities derivable from MPC. This study first reviews the different weighting factor design techniques proposed in the literature for power electronics and electrical drives (applied to wind/solar energy conversion, microgrids, grid-connected converters and other high performance converter-based systems). They are grouped under heuristic, offline tuning, sequential, and online optimization methods. Next, the study provides real-time hardware-in-the-loop comparative results for the implementation of four weighting factor design techniques on a grid-connected two-level back-to-back power converter-based permanent magnet synchronous generator wind turbine system. Through these laboratory results, the advantages and limitations of the different weighting factor design methods are highlighted.