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

Identifiers

Collections

Citation

Export

Metrics

44

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

Identifiers

Collections

Citation

Export

Share

Metrics

44