The detection of interturn stator faults in doubly-fed induction generators

Presently, many condition monitoring techniques that are based on steady-state analysis are being applied to wind generators. However, the operation of wind generators is predominantly transient, therefore prompting the development of non-stationary techniques for fault detection. In this paper we apply steady-state techniques, e.g. motor current signatures analysis (MCSA) and the extended Park's vector approach (EPVA), as well as a new transient technique that is a combination of the EPVA, the discrete wavelet transform and statistics, to the detection of turn faults in a doubly-fed induction generators (DFIG). It is shown that steady-state techniques are not effective when applied to DFIG's operating under transient conditions. The new technique shows that stator turn faults can be unambiguously detected under transient conditions.