Enhancing the Performance of a Wind Turbine Based DFIG Generation System Using an Effective ANFIS Control Technique - Ouhssain, Said; Chojaa, Hamid; Aljarhizi, Yahya; Al Ibrahmi, Elmehdi; Maarif, Alfian; A. Mossa, Mahmoud (Association for Scientific Computing Electronics and Engineering (ASCEE), 2024)
This paper gives a look on producing energy using wind turbines and imposing robust Maximum Power Point Tracking (MPPT) technique to operate around an optimal rotational speed. A mechanical speed control based on PI controller is presented in order to extract the maximum power and optimizing the conversion efficiency of wind's kinetic energy into electric energy. A doubly-fed induction generator (DFIG) is utilized because it is preferable for applications in wind energy systems referring to the capability to regulate the output voltage and improve the stability of the grid. Its operational characteristics and the regulating procedures such as Indirect Vector Control (IVC) and other sophisticated strategies for instance the ANFIS controller enhance operating flexibility and optimum performance under diverse conditions. This has attributed the split to the improved ANFIS in that it includes the artificial neural networks besides the fuzzy logic since they improve on learning as well as parameter fine tuning. Some of them are working with a comparatively fewer number of data sets; and therefore, it can be useful in classification, modeling and control. This configuration enables to regulate the generator's magnetic flux, torque, and reactive power, adjusting to changes inside wind velocity and disruptions within the grid. The performance of the proposed MPPT-IIVC method is examined by way of simulations in Matlab/Simulink. The simulations concerned a dynamic model incorporating the wind turbine, the DFIG, and the electric grid. The results show that the proposed technique can incredibly enhance the wind energy, maintain precise regulation over speed, and effectively adjust and regulate grid voltage and frequency. The performance of the proposed ANFIS controller is compared with a PI controller and discovered that ANFIS enhances the robustness, precision, dynamic response, total harmonic distortion THD (%) of the injected current into the grid, the reference tracking ability and Overshoot (%).