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.