Characterization of Power Transformer Frequency Response Signature using Finite Element Analysis

Power transformers are a vital link in electrical transmission and distribution networks. Monitoring and diagnostic techniques are essential to decrease maintenance and improve the reliability of the equipment.This research has developed a novel, versatile, reliable and robust technique for modelling high frequency power transformers. The purpose of this modelling is to enable engineers to conduct sensitivity analyses of FRA in the course of evaluating mechanical defects of power transformer windings. The importance of this new development is that it can be applied successfully to industry transformers of real geometries

Impact of Axial Displacement on Power Transformer FRA Signature

Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a singlephase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model’s parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer

Understanding power transformer frequency response analysis signatures

This paper presents a comprehensive analysis of the effects of various faults on the FRA signatures of a transformer simulated by a high-frequency model. The faults were simulated through changes in the values of some of the electrical components in the model. It was found that radial displacement of a winding alters the FRA signature over the entire frequency range (10 Hz-1 MHz), whereas changes due to axial displacement occur only at frequencies above 200 kHz. A Table listing various transformer faults and the associated changes in the FRA signature was compiled and could be used in the formulation of standard codes for power transformer FRA signature interpretation

Detection of power transformer disk space variation and core deformation using frequency response analysis

Frequency response analysis (FRA) has become a widely accepted tool to detect power transformer winding deformation due to the development of FRA test equipment. Because FRA relies on graphical analysis, interpretation of its signature is a very specialized area that calls for skilled personnel, as so far, there is no reliable standard code for FRA signature classification and quantification. Many researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature by changing particular electrical parameters of the transformer equivalent electrical circuit. None of them however, investigated the impact of physical fault levels on the transformer FRA signature as it is very difficult to implement faults within real transformer without damaging it. In this paper, the physical geometrical dimension of a power transformer is simulated using 3D finite element analysis to emulate the real transformer operation. Physical core deformation and disk space variation are simulated and the impact of each fault on the transformer FRA signature is investigated

Finite-Element Performance Evaluation of On-Line Transformer Internal Fault Detection Based on Instantaneous Voltage and Current Measurements

This paper investigates the performance of a recently proposed online transformer internal fault detection technique through detailed non-linear three-dimensional finite element modelling of the windings, magnetic core and transformer tank. The online technique considers correlation of transformer instantaneous input and output voltage difference and input current at the power frequency and uses the ellipse shape ΔV-I locus as the finger print of the transformer that could be measured every cycle to identify any incipient faults. The technique is simple, fast and suitable for online monitoring of in-service transformers. A detailed three-dimensional finite element model of single-phase transformer is developed and various physical winding deformations with different fault levels are simulated to assess their impacts on the online ΔV-I locus. As transformer field testing under various internal fault conditions cannot be easily conducted, the main contributions of this paper are accurate finite element based implementation, testing and performance evaluation of the online fault detection approach. Furthermore, the impact of winding short circuit fault on the ΔV-I locus has been also measured and validated