Performance analysis of a robust adaptive fuzzy logic controller for wind turbine power limitation

Abstract Power limitation and load reduction are considered the main challenges for the large scale wind turbine when the system operates in the above rated wind speeds. The controller design still a complex and critical task in the presence of the system nonlinearities and the wind turbulent behavior to produce a cleaner energy without switching harmonics. In this context, an adaptive controller based on fuzzy logic concept is proposed to limit the extracted power at rated value with improving its quality and to mitigate the loads applied on the turbine and the drive train in full loads conditions by adjusting the pitch angle. First, the different parts of the DFIG wind system are modeled. Thereafter, the main control structures in different operating regions are briefly described. The second part is focused on the pitch control technique. The initial parameters of fuzzy logic controller (FLC) are defined based on literature studies. Then, those parameters are tuned to derive the optimized FLC. Finally, the scaling factors of this last configuration are automatically adjusted by means of a correction factor to develop the Adaptive FLC. By the end, a technical and economic comparative studies are conducted between the three fuzzy controller configurations and the classical structures which are classical PI controller and Gain scheduled PI controller using several performance indicators. The responses assessment obtained from virtual simulation using MATLAB/SIMULINK show that the adaptive FLC is the best solution for the pitch control in terms of rapidity, stability and robustness and allow producing higher electrical energy with lowest harmonics rate.