Performance Evaluation of Model Predictive Control for Neutral-Point-Clamped Voltage Source Converter with LCL Filter

The large-scale integration of distributed power generation plants based on Renewable Energy Sources (RES) increases the overall system complexity and poses a growing challenge for maintaining a stable and reliable electricity supply. In particular, solar and wind energy systems come along with high intermittency, are subjected to stochastic fluctuations and thus increase system uncertainties. Since power converters are the key system component to interface RES-based plants to the power grid, they will play a significant role in operating future power grids. Even nowadays they are already required to provide ancillary system services. Contrary, the high penetration of grid-interfaced power converters comes along with increased power quality issues. Thus, appropriate and advanced control techniques are required to meet the growing demands on future power converter operation. Technological advances allow the implementation of highly sophisticated and complex control techniques. Among them, the Model-based Predictive Control (MPC) approach proves to be a powerful and promising methodology. This work deals with MPC for grid-connected through Neutral-Point-Clamped (NPC) Voltage Source Converters (VSC) with LCL filter. The chosen MPC approach is experimentally validated on a VSC test bench.