ONLINE DIAGNOSIS OF WINDING AXIAL DISPLACEMENT IN POWER TRANSFORMERS BASED ON REAL-TIME CHANGES IN SHORT-CIRCUIT IMPEDANCE

Abstract

Power transformers represent critical assets within electrical power systems, and the implementation of online fault diagnosis has garnered considerable research interest in recent years. Short-circuit impedance stands out as a fundamental parameter significantly influencing transformer design. Under the intense electromagnetic forces arising during short-circuit events, transformer windings are susceptible to deformation, with axial displacement being a prominent type of damage. Such axial displacement can induce measurable alterations in the transformer's short-circuit impedance. This paper presents an investigation into the online diagnosis of winding axial displacement in power transformers by analyzing real-time changes in short-circuit impedance. Utilizing finite element method (FEM) simulations, the study compares various components of the leakage flux density, the net leakage flux density, percentage reactance, and percentage impedance. The sensitivity and monotonic behavior of these parameters with respect to axial displacement in both the low-voltage and high-voltage windings are thoroughly evaluated.