Predictive control strategy for DFIG wind turbines with maximum power point tracking using multilevel converters

This paper proposes a control scheme for a wind turbine using a DFIG electromechanical converter, implemented through an NPC three-level back to back converter, that keeps a unitary power factor injection to the grid and maximizes the energy harvested from wind, using a maximum power point tracking algorithm (MPPT). A predictive direct power control (DPC) strategy drives the grid-side converter, to maintain the DC bus reference voltage. Whereas, a predictive direct torque control (DTC) strategy drives the machine-rotor-side converter, to control the power extraction, the power factor and balancing of the DC bus capacitors. The developed model allows to study the wind energy conversion system (WECS) for energy harvesting, rotor dynamics and power quality analysis. Simulation results endorse the effectiveness of the advanced control techniques for the whole wind spectrum, including the pitch angle control. A sensitivity analysis shows that the predictive DTC control strategy is robust with an uncertainty up to 20% of the induction machine parameters.