Maximum Power Point Tracking Techniques Based on M5P Indirect Control of Doubly Fed Induction Generator for Wind Energy Systems

This study introduces M5P a control method to excerpt maximum capacity by wind power. Two methods of Utmost potency point tracking, is examined in detailed (with or without speed control). A regression model tree algorithm based on M5P fuzzy logic has been inserted into indirect control doubly fed induction generator. An integrated M5P machine learning algorithm to overcome the classic dynamic disadvantages of traditional controllers and to reduce the computational complexity, thereby improving the dynamics and robustness of the doubly fed induction generator while ensuring optimal operation of the wind turbine. Finally, the modeling and global control of the 2MW is achieved for the two operating modes hypo- and hyper-synchronous. The results obtained showed that they could have an optimal active power supplied to the electrical network regardless of the operating mode of the generator.