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

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.