Online Monitoring of Partial Discharges in Large Power Transformers Using Ultra-High Frequency and Acoustic Emission Methods: Case Studies

Partial discharges (PDs) are one of the leading causes of catastrophic power transformer failures. To prevent such failures, online PD monitoring systems are increasingly being implemented. In this paper, to the best of the authors’ knowledge, a case study analysis of short-term PD monitoring is presented for the first time using a combination of acoustic emission and ultra-high-frequency methods. Studies have shown that this approach, supported by selected statistical methods for analyzing the convergence (such as the confusion matrix and agreement metrics) of acoustic and electromagnetic pulse detection, improves the reliability of PD detection. Furthermore, it was shown that short-term PD monitoring enables the identification of time windows during which discharges occur periodically and the determination of the transformer phase containing the PD source. This, in turn, facilitates the application of the time difference of arrival (TDoA) technique for the precise localization of transformer insulation defects.