Nonlinear Model Predictive Control Applied to a DFIG-Based Wind Turbine With a Shunt APF

The present paper describes a wind turbine coupled to a Doubly Fed Induction Generator (DFIG) connected to the electric power grid via a Shunt Active Power Filter (SAPF). The studied system is controlled by two controllers based on the approach of the nonlinear model predictive control (NMPC). The NPC applied to the DFIG is designed to ensure optimum performances of the DFIG. While the NPC applied to the SAPF is developed to compensate the harmonic produces by the nonlinear load. The control laws are obtained by optimization of the two cost functions based on the prediction error, which contains the difference between the predicted outputs and its references. A Taylor series expansion is exploited to define the predicted outputs of the system in order to ensure a perfect tracking of the rotor speed and the rotor current regulation, also to obtain the sinusoidal waveform of the stator voltage and stator current. The performances of the NPCs are studied via simulation on the environment Matlab/Simulink. We obtained satisfying results that show the benefits of using an NPC.