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

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

San Juan, San Juan

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

IEEE

Abstract? Currently, there are online and offline techniquesfor transformer fault diagnosis. However, offline tests havetraditionally been the most frequently used. In recent years,online fault detection and diagnosis techniques based on themonitoring of electrical variables have arisen, with greatpotential to prevent transformer faults. Such techniques havebeen i mplemented and analyzed independently either throughcomputational simulations or experimental tests. Moreover, thevalidations 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 ofthe main alternatives presented in the literature. The comparisonis carried out through computational simulations with asimplified model of the transformer. This allows analyzing eachtechnique under identical conditions. The comparison is focusedexclusively on inter-turn short-circuits, which is statistically themost recurrent fault in this type of machines. The conclusionsreached make it possible to weigh the strengths and weaknessesof each of the techniques analyzed.