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Autor(en): Tahir, Mehran
Tenbohlen, Stefan
Titel: A comprehensive analysis of windings electrical and mechanical faults using a high-frequency model
Erscheinungsdatum: 2019
Dokumentart: Zeitschriftenartikel
Seiten: 25
Erschienen in: Energies 13 (2019), No. 105
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-136282
http://elib.uni-stuttgart.de/handle/11682/13628
http://dx.doi.org/10.18419/opus-13609
ISSN: 1996-1073
Zusammenfassung: The measurement procedures for frequency response analysis (FRA) of power transformers are well documented in IEC and IEEE standards. However, the interpretation of FRA results is still far from reaching an accepted methodology and is limited to the analysis of the experts. The dilemma is that there are limited case studies available to understand the effect of different faults. Additionally, due to the destructive nature, it is not possible to apply the real mechanical deformations in the transformer windings to obtain the data. To solve these issues, in this contribution, the physical geometry of a three-phase transformer is simulated using 3D finite integration analysis to emulate the real transformer operation. The novelty of this model is that FRA traces are directly obtained from the 3D model of windings without estimating and solving lumped parameter circuit models. At first, the method is validated with a simple experimental setup. Afterwards, different mechanical and electrical faults are simulated, and their effects on FRA are discussed objectively. A key contribution of this paper is the winding assessment factor it introduces based on the standard deviation of difference (SDD) to detect and classify different electrical and mechanical faults. The results reveal that the proposed model provides the ability of precise and accurate fault simulation. By using SDD, different deviation patterns can be characterized for different faults, which makes fault classification possible. Thus, it provides a way forward towards the establishment of the standard algorithm for a reliable and automatic assessment of transformer FRA results.
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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