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This paper proposes a H∞ Fuzzy robust controller for Doubly Fed Induction Generator (DFIG) based wind turbines. The power exchange between the machine stator and the grid is carried out by acting on the rotor via a bidirectional converter. The control objective is to regulate the stator active and reactive power generated from the DFIG by means of two kinds of controllers named H∞ PI and H∞ Fuzzy. Comparison study between the proposed controllers considering reference tracking and robustness to parameter variations is discussed. Simulation results illustrate the effectiveness of the H∞ Fuzzy controller compared with the other one for time-varying reference tracking and parameters variations, which improves quality and quantity of generated power. [ABSTRACT FROM AUTHOR]

In wind energy systems, it is necessary to have a good knowledge of the used generator and its parameters. Despite the motor manufacturer's specifications, accurately estimating the machine parameter reference values is critical for the perfect control system. In this context, off-line identification tests of a 3 kW permanent magnet synchronous machine were conducted to determine the mechanical and electrical parameters. In addition, this research exploits a meta-heuristic optimization technic dubbed grey wolf optimizer in the on-line parameter's identification field. The estimate method is focused on the parameter's estimation linked to a reference model. The rule is based on the cancelation of the current error among the measured and the associated estimated current. For each measurement, the grey wolf estimator adapts the reference model parameters until the model response and the accurate response be similar. All were implemented using the real-time interface of the DSpace DS1104 Controller card while using the ControlDesk graphical user interface and the Simulink/MATLAB environments. Results from hardware simulation confirm the efficacy and benefits of the suggested strategy. [ABSTRACT FROM AUTHOR]