LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control

Power generation losses arise in doubly fed induction generator (DFIG) system due to grid faults. The system’s protection should ensure that the wind turbine (WT) generator meets the grid requirements through a low voltage ride through (LVRT) technique. This article proposes the feed-forward neuro-s...

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Autores principales:	Hiremath Ravikiran, Moger Tukaram
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	wt dfig lvrt ffn sosm Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/b63622aec88349569479427dc2281e36
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spelling	oai:doaj.org-article:b63622aec88349569479427dc2281e362021-12-05T14:10:47ZLVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control2391-543910.1515/eng-2021-0100https://doaj.org/article/b63622aec88349569479427dc2281e362021-10-01T00:00:00Zhttps://doi.org/10.1515/eng-2021-0100https://doaj.org/toc/2391-5439Power generation losses arise in doubly fed induction generator (DFIG) system due to grid faults. The system’s protection should ensure that the wind turbine (WT) generator meets the grid requirements through a low voltage ride through (LVRT) technique. This article proposes the feed-forward neuro-second order sliding mode (FFN-SOSM) control for the LVRT enhancement under voltage sag. This controller operates with the levenberg marquardt (LM)-super twisting (ST) algorithm for the uncertainties of the DFIG system. The LM-ST algorithm-based proposed controller is subjected to stability analysis. The advantages of the proposed controller are that it reduces the system parameter’s peak values and harmonic distortion of the system during grid disturbance. The performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the LVRT performance of the WT-DFIG system under transient conditions.Hiremath RavikiranMoger TukaramDe GruyterarticlewtdfiglvrtffnsosmEngineering (General). Civil engineering (General)TA1-2040ENOpen Engineering, Vol 11, Iss 1, Pp 1000-1014 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	wt dfig lvrt ffn sosm Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	wt dfig lvrt ffn sosm Engineering (General). Civil engineering (General) TA1-2040 Hiremath Ravikiran Moger Tukaram LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
description	Power generation losses arise in doubly fed induction generator (DFIG) system due to grid faults. The system’s protection should ensure that the wind turbine (WT) generator meets the grid requirements through a low voltage ride through (LVRT) technique. This article proposes the feed-forward neuro-second order sliding mode (FFN-SOSM) control for the LVRT enhancement under voltage sag. This controller operates with the levenberg marquardt (LM)-super twisting (ST) algorithm for the uncertainties of the DFIG system. The LM-ST algorithm-based proposed controller is subjected to stability analysis. The advantages of the proposed controller are that it reduces the system parameter’s peak values and harmonic distortion of the system during grid disturbance. The performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the LVRT performance of the WT-DFIG system under transient conditions.
format	article
author	Hiremath Ravikiran Moger Tukaram
author_facet	Hiremath Ravikiran Moger Tukaram
author_sort	Hiremath Ravikiran
title	LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
title_short	LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
title_full	LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
title_fullStr	LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
title_full_unstemmed	LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
title_sort	lvrt enhancement of dfig-driven wind system using feed-forward neuro-sliding mode control
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/b63622aec88349569479427dc2281e36
work_keys_str_mv	AT hiremathravikiran lvrtenhancementofdfigdrivenwindsystemusingfeedforwardneuroslidingmodecontrol AT mogertukaram lvrtenhancementofdfigdrivenwindsystemusingfeedforwardneuroslidingmodecontrol
_version_	1718371741767565312

LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control

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