DocumentCode :
2131860
Title :
Induction generator rotor faults modeling and diagnosis based on double PQ transformation
Author :
Leksir, A. ; Bensaker, B.
Author_Institution :
Dept. of Electron., Univ. of Annaba, Annaba, Algeria
fYear :
2011
fDate :
7-9 April 2011
Firstpage :
1
Lastpage :
6
Abstract :
This work deals with PQ state space modeling of asynchronous generator for rotor faults detection and diagnosis. Asynchronous generator is one of the mostly used machines as electrical power generator. This is due to its low cost and high reliability compared to other types of renewable energy sources. In order to ensure reliable and profitable operations, asynchronous generator must be carefully surveyed. The main major asynchronous generator faults are the rotor broken bars, the stator shorted turns and the air-gap eccentricities. The proposed method uses stator current to estimate the remaining state variables that are related to active and reactive power of the machine. In this context different models of the machine operating conditions are discussed from the theoretical point of view. Observer state estimation technique is used to reconstruct the non measured state variables of the machine. A simulation example is presented to point out the merits of the proposed double PQ transformation method.
Keywords :
asynchronous generators; electric power generation; fault diagnosis; machine theory; reactive power; rotors; state estimation; stators; air-gap eccentricities; asynchronous generator; double PQ transformation; electrical power generator; induction generator rotor fault modeling; reactive power; renewable energy sources; rotor faults detection; rotor faults diagnosis; stator current; Electromagnetics; Inductance; Induction generators; Reactive power; Rotors; Stators; Faults Diagnosis; Induction Generator; PQ transformation; Power Modeling; State observer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2011 International Conference on
Conference_Location :
Ouarzazate
ISSN :
Pending
Print_ISBN :
978-1-61284-730-6
Type :
conf
DOI :
10.1109/ICMCS.2011.5945572
Filename :
5945572
Link To Document :
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