AN IMPROVED DECISION MAKING ALGORITHM FOR ON LINE DISCRIMINATION BETWEEN INRUSH AND FAULT CURRENT IN A TRANSFORMER: DWT APPROACH

Transformer protection is critical issue in power system and the issue lies in the accurate and rapid discrimination of magnetizing inrush current from internal fault current. This paper describes a new method to discriminate the magnetizing inrush current and interturn fault using the wavelet transform. This method is independent of setting any threshold for discrimination amongst these. A discriminating function and feature extraction is defined in terms of difference of two-peak amplitude of wavelet coefficients in a specific frequency band. Interturn faults were staged at various time instants and it was observed that the strategy holds good for all instants i.e. it is independent of instant of occurrence of fault also. This discrimination will aid in development of an automatic detection method and shall give information to predict the failure ahead of time so that the necessary corrective actions are taken to prevent outages and reduce down time. This paper also presents a comparison of two algorithms to discriminate magnetizing inrush current from interturn fault current, based on wavelet coefficients as a discriminating function, A) where two peak values corresponding to the |d5| level following the fault instant is used as a discriminating feature, and B) where difference of two peak amplitude of wavelet coefficients of fast cross-correlated signal at |d4| level is used as a discriminating feature. The performance of this algorithm is demonstrated on custom-built mains feed single-phase transformer, used in the laboratory to collect the data from controlled experiments. The proposed on line detection scheme is also discussed.