Nonlinear predictive control of a DFIG-based wind turbine for power capture optimization

Abstract A nonlinear predictive controller is proposed for a variable speed wind turbine. The objective is power capture optimization and transient loads reduction. The controller acts only on low wind speed area. It consists of a doubly fed induction generator controller coupled with a model predictive aeroturbine controller. Unlike the majority of existing work on DFIG, the nonlinear controller deals directly with the generator model without any simplifying assumptions. This makes it possible to remove some assumptions on the DFIG model. The nonlinear DFIG controller achieves asymptotic torque and flux tracking. For the aeroturbine part, the model predictive controller uses predictions of the output to compute the optimal control sequence. It makes a compromise between power capture optimization and loads reduction. The controllers design procedure is detailed. The global controller is tested with the parameters of a real experimental variable speed wind turbine. It is compared with PID and LQG controllers. The simulations show satisfactory results in comparison with these schemes. The proposed controller achieves better power capture optimization and load reduction. It therefore allows a good achievement of the design objectives.