Comparison of Online Techniques for the Detection of Inter-Turn Short Circuits in Transformers

GUSTAVO LEAL; CARLOS VERUCCHI; GUILLERMO BOSSIO; MATIAS MEIRA; CRISTIAN RUSCHETTI

San Juan

Congreso; XIX Reunión de Trabajo en Procesamiento de la Información y Control (RPIC2021); 2021

Currently, there are online and offline techniques for transformer fault diagnosis. However, offline tests have traditionally been the most frequently used. In recent years, online fault detection and diagnosis techniques based on the monitoring of electrical variables have arisen, with great potential to prevent transformer faults. Such techniques have been implemented and analyzed independently either through computational simulations or experimental tests. Moreover, the validations of each of them were performed in transformers of different ratings, voltage levels and under completely different conditions. This paper presents a critical comparison of some of the main alternatives presented in the literature. The comparison is carried out through computational simulations with a simplified model of the transformer. This allows analyzing each technique under identical conditions. The comparison is focused exclusively on inter-turn short-circuits, which is statistically the most recurrent fault in this type of machines. The conclusions reached make it possible to weigh the strengths and weaknesses of each of the techniques analyzed.