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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.

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.

International audience; The purpose of this work is to compare some linear and nonlinear control strategies, with the aim of benefiting as well as possible of wind energy conversion systems. Below rated wind speed, the main control objective is to perform an optimal wind power capture while avoiding strong loads on the drive train shafts. To explicitly take into consideration the low speed shaft flexibility, a two-mass nonlinear model of the wind turbine is used for controllers synthesis. After adapting a LQG controller based on the linearized model, nonlinear controllers based on a wind speed estimator are developed. They take into account the nonlinear dynamic aspect of the wind turbine and the turbulent nature of the wind. The controllers are validated upon an aeroelastic wind turbine simulator for a realistic wind speed profile. The study shows that nonlinear control strategies bring more performance in the exploitation of wind energy conversion systems.

A cascaded nonlinear controller is designed for a variable speed wind turbine equipped with a Doubly Fed Induction Generator (DFIG). The main objective of the controller is wind energy capture optimization while avoiding strong transients in the turbine components and specially in the drive train. The inner loop controller ensures an efficient tracking of both generator torque and stator flux, while the outer loop controller achieves a close tracking of the optimal blade rotor speed to optimize wind energy capture. It is combined to a wind speed estimator that provides an estimation of the wind speed and the aerodynamic torque involved in the controller. The global controller is firstly tested with a simplified mathematical model of the aeroturbine and DFIG for a high-turbulence wind speed profile. Secondly, the aeroturbine controller is validated upon a flexible wind turbine simulator. These new control strategies are compared to other existing controllers based on tests upon an aeroelastic wind turbine simulator. The obtained results show better performance in comparison with the existing controllers.

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.

International audience

Reliable and powerful control strategies are needed for wind energy conversion systems to achieve maximum performance. A new control strategy for a variable speed, variable pitch wind turbine is proposed in this paper for the above-rated power operating condition. This multivariable control strategy is realized by combining a nonlinear dynamic state feedback torque control strategy with a linear control strategy for blade pitch angle. A comparison with existing strategies, PID and LQG controllers, is performed. The proposed approach results in better power regulation. The new control strategy has been validated using an aeroelastic wind turbine simulator developed by NREL for a high turbulence wind condition.

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