Dip voltage fault detection and identification for wind generator turbine farm based on current vector trajectory analysis

Arnel Adouni; Demba Diallo; Lassaad Sbita

doi:10.1109/IREC.2015.7110908

Conference papers

Dip voltage fault detection and identification for wind generator turbine farm based on current vector trajectory analysis

Arnel Adouni ¹ Demba Diallo ² Lassaad Sbita ¹

1 SPEG - Unite de recherche, système photovoltaïque éolien et géothermique

2 GeePs - Laboratoire Génie électrique et électronique de Paris

Abstract : This paper focuses on the voltage dip diagnosis in a Wind Generator Turbine Farm. The proposed approach is based on the analysis of the grid currents vector trajectory in the stationary reference frame. Two features are used; the diameter variation for fault detection and the angle deviation for fault isolation. The approach is validated through simulation results of a two Doubly Fed Induction Generator and generalized for N Machines.

Keywords : Wind Generator Turbine Farm dip voltage fault detection and identification current analysis

Document type :

Conference papers

Domain :

Engineering Sciences [physics]

Complete list of metadatas

https://hal-centralesupelec.archives-ouvertes.fr/hal-02402593
Contributor : Amandine Lustrement <>
Submitted on : Tuesday, December 10, 2019 - 3:14:30 PM
Last modification on : Wednesday, September 16, 2020 - 5:51:56 PM

Dip voltage fault detection and identification for wind generator turbine farm based on current vector trajectory analysis

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Dip voltage fault detection and identification for wind generator turbine farm based on current vector trajectory analysis

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