Soft ware based technique for the identification of transformer faults in real time

Abstract

Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by considering the voltage-current (V-I) locus diagram as a transformer fingerprint that can be measured every cycle to provide a current state of the transformer. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault. The proposed technique is easy to implement and automated so that the requirement for expert personnel can be eliminated.