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Wind turbine torque control strategy is commonly used to maximize energy in low wind speed operating. One of the main limitations of wind turbine control is wind fluctuations, in order to solve this problem, the present article represents a fuzzy gain scheduling of PI gains (FGSPI) for torque control based on tip-speed ratio (TSR) method. This technique consists in choosing the optimal gains by using human expertise based on fuzzy rules. Controls Advanced Research Turbine (CART) based on the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) simulator developed at the National Renewable Energy Laboratory (NREL) in the United States is used for simulations. The results show that the proposed method performs well compared to the conventional method with better monitoring of the reference speed and load mitigation.

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.

In this work we present the remote control of the tank level system. The physical system is controlled in real time using local or Internet network. The client could manage the remote experiment through a simple web browser via a graphical shared user interface. The study is based on the PID identification parameters according to Ziegler-Nichols methods. After the identification of the PID parameters the experiment is tested and the result are given.

To maximize wind power extraction, a variable-speed wind turbine (VSWT) should operate as close as possible to its optimal power coefficient. The generator torque is used as a control input to improve wind energy capture by forcing the wind turbine (WT) to stay close to the maximum energy point. In general, current control techniques do not take into account the dynamical and stochastic aspect of both turbine and wind, leading to significant power losses. In addition, they are not robust with respect to disturbances. In order to address these weaknesses, a nonlinear approach, without wind speed measurement for VSWT control, is proposed. Nonlinear static and dynamic state feedback controllers with wind speed estimator are then derived. The controllers were tested with a WT simple mathematical model and are validated with an aeroelastic wind turbine simulator in the presence of disturbances and measurement noise. The results have shown better performance in comparison with existing controllers.

In this paper, a remote temperature control system has been proposed. The physical system is controlled in real time through the Internet network. For educational purpose, the students use only a web browser to tune and test a PID controller via shared user interface. The PID parameters are calculated using the basic experimental Ziegler—Nichols tuning rules. After hardware and software experiment description, the remote online experiment is tested and the results are given.

A nonlinear approach, for variable speed wind turbines control, is presented by considering that there is no wind speed measurement. The control objective below rated wind speed is to maximize the extracted energy from the wind while reducing mechanical loads. The existing control techniques do not take into account the dynamical aspect of the wind and the turbine, which leads to significant power losses, besides, they are not robust. In order to bring some improvement and to evaluate the applicability efficiency of the nonlinear controllers, so then, nonlinear static and dynamic state feedback controllers with wind speed estimator are derived. The controllers are tested upon a mathematical model and are validated with a wind turbine simulator, in presence of disturbances and measurement noise. The results indeed show significant improvements in comparison with the existing controllers.

A nonlinear controller has been designed for variable speed wind turbines electric power regulation. The efficiency and reliability of wind power is shown to be depending on the applied control strategy of the wind turbine. Up to now, classical regulation is implemented only. However, under sudden wind profile variations, the wind turbine performance decrease which may cause troubles in the electrical network. For the limitation of mechanical loads and rotational speed variations, and to avoid the wind turbine stall above rated wind speeds while controlling the output power, a cascade structure asymptotic output tracking based approach has been applied. Simulations and validation have been performed using the wind turbine modelling and using wind turbine simulator as well. The wind turbine is torque generator controlled. The required performance is met for both

International audience

International audience

International audience