Feasibility study for partial discharge detection and defective region identification in power transformers by using distributed sensors

Abstract

Monitoring of partial discharge (PD) and its progress as the main cause of the insulation deterioration process in power transformers can encompass valuable information about the related insulation condition and reveals degradation mechanisms. In this study, some simple sensors, which are made from a few turns wrapped around the transformer core, are used to detect PD signals. Moreover, a feasibility study is done to identify defective phase/region based on the captured PD signals waveforms through these sensors. The idea is implemented on a 50 kVA, 20 kV/400 V three-phase transformer by injecting artificial and quasi-real PD signals to different sections of HV windings. Also, various transformer connections are considered in the experimental studies to find the effect of them on the waveforms of the captured signals (e.g. peak-to-peak value and signal energy). The obtained experimental results show that small PDs (as low as 10 pC) is detectable by the mentioned sensors and defective phase can be identified in all of transformer connection cases. Furthermore, considering failure to identify defective regions by broadband analysis, a limited-band approach is proposed through obtaining |H(s)| for the sensors. The results show that exact defective phase/region identification is feasible by selecting a frequency band compatible with IEC60270 recommendation.