Intelligent Control for Doubly Fed Induction Generator Connected to the Electrical Network - Anass Bakouri; Hassane Mahmoudi; Ahmed Abbou (International Journal of Power Electronics and Drive Systems (IJPEDS), 2016)
In this paper we are interested in optimizing the wind power capture, using the Doubly Fed Induction Generator (DFIG). This machine is preferred to other types of variable speed generator because of their advantages in economic terms and control. The Artificial Neural Network (ANN) based on Direct Torque Control (DTC) which is used to control the electromagnetic torque in order to extract the maximum power, The  main  objective  of this intelligent technique is to replace the conventional switching table  by  a  voltage  selector  based  on  (ANN)  to  reduce torque  and  flux  ripples. Moreover, the fuzzy logic controller is used to grid side converter to keep DC link voltage constant, and also to achieve unity power factor operation. The main advantage of the two control strategies proposed in this paper is that they are not influenced by the variation of the machine parameter. The pitch control is also presented to limit the generator power at its rated value. Simulation results of 1,5 MW, for (DFIG) based Wind Energy Conversion System (WECS) confirm the effectiveness and the performance of the global proposed approaches.