A signal processing technique for PD detection and localization in power transformer winding

Abstract

Precise detection and localization of faults in power transformer windings for ultimate protection is the key issue. The insulation quality in windings majorly determines the enduring transformers function. Achieving as accurate and efficient detection method of partial discharge (PD) in transformer windings is challenging. The occurrence of PD being primarily responsible for the transformers failure its detection is considered as preventive measure to avoid large-scale economic losses. This paper briefly overviews the salient features of the conventional acoustic and travelling wave methods those electrically determine the dominant capacitive region in the frequency domain. We propose a technique which is based on the PD signal detection and the measurement of the characteristics transfer functions in the frequency domain. A distributed circuit transformer model with eight sections is developed and simulated via Matlab code. PD signals analogous to sources in various locations are injected at different points within the transformer windings. The PD source positions are determined in terms of the number of turns from the line-end. The determination of PD locations on the basis of zero frequency differences is demonstrated. Our method significantly improved the accuracy to identify the PD location. The limitations associated with the appearance of noise and the frequency range for detection is overcome. The occurrence of crests and troughs in the frequency spectra are used to locate the source of PD activity in transformer windings.