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This work presents a control strategy for Wind Turbine (WT) power by using an algorithm of Indirect Maximum Power Control (IMPC). This algorithm is based on Tip Speed Ratio (TSR) approach, which is applied to control wind turbines. Indeed, the WT used in this study has a single mass brought back to the generator shaft. The main contribution of this study is to maximize the aerodynamic power delivered by the WT system. In fact, this maximization is carried out during partial load operation, without consideration of the disturbances caused by variations in the wind profile. In this context, the control strategy of the WT is performed by estimating the Wind Speed (WS) instead of using an anemometer. This estimation is handled by using an Adaptive Gain Sliding Mode Control (AG-SMC). For this control, the surface is chosen as an improved solution that carried out the adaptation for the sliding gain and the generator torque estimation. The results obtained in Matlab / Simulink software showed that the aerodynamic power maximum is achieved and the control algorithm IMPC is given a high efficiency in the WS estimation.

The present paper aims to improve the effectiveness of an isolated water pumping system based on parallel wind turbine powertrains by using a nonlinear Integral Backstepping Controller (IBSC). In fact, the powertrain system with parallel Permanent Magnet Synchronous Generators (PMSG) is used to ensure the continuity of the power conversion system and to optimize the efficiency of generators. A three-phase PWM rectifier is implemented in the power system to convert the AC voltage obtained from parallel PMSG generators to a DC voltage. In fact, the regulated DC voltage will be supplied to a DC motor-driven water pump to control the tank level in the wind turbine pumping system. In this paper, the effective wind speed of a wind turbine is estimated by using an Extended Kalman Filter (EKF) instead of using anemometers. In addition, the Tip Tip Speed Ratio (TSR) method based on an Adaptive Fuzzy Logic Controller (AFLC) is performed to apply the Maximum Power Point Tracking (MPPT) algorithm for maximum power extraction from the available energy in the wind. Moreover, the Voltage Oriented Control (VOC) strategy is handled to control the currents of the three-phase rectifier. To evaluate the efficiency of the EKF estimator, the covariance and correlation coefficient between the estimated and measured wind speed are computed for each s 1 , while the AFLC and nonlinear IBSC controllers are evaluated by comparing their results with those obtained by the PI controller. For the wind speed estimation, the covariance and correlation coefficient results demonstrate that the EKF estimator has high accuracy with a 98% similarity between the estimated and measured wind speed. For the power extraction, the TSR based on adaptive FLC controller can extract slightly more wind energy than the PI controller. For tank level control, the nonlinear IBSC controller improves the efficiency of the wind turbine water pumping system by reducing the DC voltage surge and the overshoot of water level obtained by PI controller.