Hybrid modelling of doubly fed induction generators with inter-turn stator fault and its detection method using wavelet analysis

• Published in: IET generation, transmission & distribution Vol. 7; no. 9; pp. 982 - 990
• Main Authors: Yousefi kia, Mohammad, Khedri, Mostafa, Najafi, Hamid Reza, Shamsi Nejad, Mohammad Ali
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.09.2013; Institution of Engineering and Technology; The Institution of Engineering & Technology
• Subjects: Applied sciences; asynchronous generators; condition monitoring; DFIG; doubly fed induction generator; Electrical engineering. Electrical power engineering; electrical machine failure; Electrical machines; Exact sciences and technology; failure analysis; Fault detection; fault detection index; Faults; High voltage or high current generators; hybrid modelling; Induction generators; interturn stator fault detection; Miscellaneous; Modelling; power generation faults; power generation reliability; rotor resistance; rotors; Sampling; sampling frequency; signal sampling; Stators; steady‐state condition; Testing. Reliability. Quality control; Various equipment and components; Wavelet analysis; wavelet transforms; doubly fed induction generator; power generation reliability; rotors; electrical machine failure; wavelet transforms; fault detection index; interturn stator fault detection; asynchronous generators; steady-state condition; sampling frequency; failure analysis; rotor resistance; stators; hybrid modelling; wavelet analysis; signal sampling; condition monitoring; power generation faults; DFIG; Asynchronous generators; Stator; Absorbing boundary condition; Failures; Modeling; Rotor; Steady state; Sampling frequency; Wavelet transformation; Electric machine; Double supply machine; Hybrid model; Signal analysis; Monitoring; Defect detection
• ISSN: 1751-8687; 1751-8695
• DOI: 10.1049/iet-gtd.2012.0491

Stator faults contribute to 38% of all electrical machine failures. The detection of inter-turn stator fault has therefore been the focus of research for many years. The aim of this research is to provide new condition monitoring technique for doubly fed induction generator during inter-turn fault. The contribution of this research is to formulate a method of doubly-fed induction generator (DFIG) inter-turn stator fault detection that is applicable when this machine operates during steady-state condition. New proposed hybrid model (ABC/dq) has been presented for modelling of DFIG with inter-turn stator fault. Finally a new index has been defined for the detection of inter-turn stator fault in DFIG that employs wavelet analysis of the stator currents and energy of a signal which has been called fault detection index. Proposed index is robust to variation of operating point, percentage of turn fault, stator and rotor resistance and sampling frequency.