ENHANCING WIND POWER GENERATION EFFICIENCY: A NOVEL CONTROL ALGORITHM FOR DFIG WIND TURBINES USING FUZZY LOGIC AND NONLINEAR ESTIMATION TECHNIQUES

Abstract

The control algorithm for a wind turbine equipped with a doubly fed induction generator (DFIG) is presented in detail in this study. A Gaussian radial basis function network—a nonlinear input-output mapping technique—is used to assess the wind turbine's aerodynamic parameters. A nonlinear mapping is used to predict the wind speed. It takes into account the electrical output power of the generator, its power losses, and the dynamics of the wind turbine generator (WTG) shaft system. The creation and thorough assessment of the fuzzy logic controller are part of the new control approach. In the end, the wind generation system uses the technique that this study describes. The calculated wind speed is then utilized to determine the optimal command for the DFIG rotor speed in order to maximize wind power extraction. The Doubly Fed Induction Generator's (DFIG) speed controller is suitably designed to effectively reduce the impact of low-frequency torsional oscillations. The WTG system does away with the requirement for mechanical anemometers while producing the maximum
amount of electrical power output to the grid with exceptional dependability and efficiency.