Back to Search Start Over

Neural High Order Sliding Mode Control for Doubly Fed Induction Generator based Wind Turbines.

Authors :
Djilali, Larbi
Badillo-Olvera, Anuar
Yuliana Rios, Yennifer
Lopez-Beltran, Harold
Saihi, Lakhdar
Source :
IEEE Latin America Transactions; Feb2022, Vol. 20 Issue 2, p223-232, 10p
Publication Year :
2022

Abstract

Wind energy has many advantages because it does not pollute and is an inexhaustible source of energy. In this paper Neural High Order Sliding Mode (NHOSM) control is developed for Doubly Fed Induction Generator (DFIG) based Wind Turbine (WT). The stator winding is directly coupled with the main network, whereas a Back-to-Back converter is installed to connect its rotor to the grid. The proposed control scheme is composed of Recurrent High Order Neural Network (RHONN) trained with the Extended Kalman Filter (EKF), which is used to build-up the DFIG models. Based on such identifier, the High Order Sliding Mode (HOSM) using Super-Twisting (ST) algorithm is synthesized. To show the potential of the selected scheme, a comparison study considering the NHOSM, Conventional Sliding mode (CSM), and the HOSM control is done. To ensure maximum power extractions and to protect the system, the Maximum Point Power Tracking (MPPT) algorithm and the h control are also implemented. Simulation results demonstrate the effectiveness of the proposed scheme for enhancing robustness, reducing chattering, and improving quality and quantity of the generated power. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15480992
Volume :
20
Issue :
2
Database :
Complementary Index
Journal :
IEEE Latin America Transactions
Publication Type :
Academic Journal
Accession number :
154310543
Full Text :
https://doi.org/10.1109/TLA.2022.9661461