Multiple-Vector Model Predictive Power Control for Grid-Tied Wind Turbine System with Enhanced Steady State Control Performances.

Direct Model Predictive Control (DMPC) is a promising alternative for power electronics and electric drives. It takes the switching non-linearity of the power converters and system constraints into consideration, without using an extra modulator. However, its one-switchingvector- per-control-interval character leads to big ripples of the control variables. Therefore, with a similar sampling frequency, its steady state performance is not satisfying. In this work we propose a Multiple-Vector Direct Model Predictive Power Control (MV-DMPPC) concept for the grid-side power converter control of a back-to-back converter PMSG wind turbine system, using a fully FPGA based solution. The proposed control scheme is compared with the classical DMPPC and two recently reported DMPPC scheme with duty cycle optimizations. Both simulation and experimental tests validate that, the control performances are evidently improved with the proposed MV-DMPPC solution.     «

Direct Model Predictive Control (DMPC) is a promising alternative for power electronics and electric drives. It takes the switching non-linearity of the power converters and system constraints into consideration, without using an extra modulator. However, its one-switchingvector- per-control-interval character leads to big ripples of the control variables. Therefore, with a similar sampling frequency, its steady state performance is not satisfying. In this work we propose a Multiple-Vector Direc...     »