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 ENIG - Ecole Nationale d'Ingénieurs de Gabès
2 GeePs - Laboratoire Génie électrique et électronique de Paris

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

Domains: Engineering Sciences [physics]

Arnel Adouni, Demba Diallo, Lassaad Sbita. Dip voltage fault detection and identification for wind generator turbine farm based on current vector trajectory analysis. 2015 Sixth International Renewable Energy Congress (IREC), Mar 2015, Sousse, Tunisia. pp.1-6, ⟨10.1109/IREC.2015.7110908⟩. ⟨hal-02402593⟩