Abstract

This paper presents a new contribution in the field of the optimization of the techniques of control of the wind systems and the improvement of the quality of energy produced in the grid. The Sliding Mode control technique gives quite interesting results, but its major drawback lies in the phenomenon of chattering (oscillations), which reduces the system's precision. We propose in this work a solution to cancel this chattering phenomenon by the implication of the adaptive Backstepping technique to control the powers of the double-fed asynchronous generator (DFIG) connected to the electrical network by two converters (network side and side machine) in the nominal part of the sliding mode model. This hybrid technique will correct errors of precision and stability and the performance of the wind system obtained in terms of efficiency, active and reactive power is significant. First, a review of the wind system was presented. Then, an exhaustive explanation of the Backstepping technique based on the Lyapunov stability and optimization method has been reported. Subsequently, a validation on the Matlab & Simulink environment was carried out to test the performance and robustness of the proposed model. The results obtained from this work, either by follow-up or robustness tests, show a significant performance improvement compared to other control techniques.

Details

Title
Robust sliding-Backstepping mode control of a wind system based on the DFIG generator
Author
Echiheb, Farah 1 ; Ihedrane, Yasmine 1 ; Bossoufi, Badre 1 ; Bouderbala, Manale 1 ; Motahhir, Saad 2 ; Masud, Mehedi 3 ; Aljahdali, Sultan 3 ; ElGhamrasni, Madiha 4 

 Sidi Mohammed Ben Abdellah University, LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Fez, Morocco 
 ENSA, SMBA University, Engineering, Systems, and Applications Laboratory, Fez, Morocco 
 Taif University, Department of Computer Science, College of Computers and Information Technology, Taif, Saudi Arabia (GRID:grid.412895.3) (ISNI:0000 0004 0419 5255) 
 Sidi Mohammed Ben Abdellah University, LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Fez, Morocco (GRID:grid.412895.3) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2688295471
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.