Purpose: In this paper, a regulate of a variable wind energy conversion system, based on a doubly fed induction generator DFIG is proposed, the system we considered is controlled to generate maximum energy while minimizing loads. In low to medium wind speeds, the generator and the power converter control the wind turbine to capture maximum energy from the wind, in the high-wind-speed regions, the wind turbine is controlled to maintain the aerodynamic power produced by the wind turbine. Generator torque and Pitch angle are controlled simultaneously to maximize energy capture. Design/methodology/approach: Two methods for adjusting the aerodynamic power have been studied: For generator load control, The DFIG control structure contains rotor currents and stator powers loops where PI controllers are used. This control could be obtained by applying a DFIG active and reactive power decoupling strategy based on stator flux orientation method, Another controller based on a sliding mode theory is adopted to maximize the extracted power has been used , both of which are employed to regulate the operation of the DFIG. For the pitch control, a nonlinear controller based on artificial intelligence techniques: genetic algorithms, to regulate the blade pitch angle and rotate speed of the wind turbine system. Findings: Proposed DFIG and pitch control algorithms provide good static and dynamic performances. Validity the strategies proposed was analyzed by simulations. Originality/value: The intelligent controller is proposed to blade pitch position control above the rated wind speed in this paper; Genetic Algorithm based controller gave better results. Simulated wind turbine parameters are obtained from a real turbine and generating system. Hence, proposed controllers can be easily adapted to real time applications and operated with real wind turbines. Compared simulation results validate the proposed method in the paper is an effective method.