05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Publication Type: search.filters.UBSTyp.ZeitschriftenartikelAuthor: search.filters.author.Tenbohlen, StefanStart date: 2019End date: 2019

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    Quantitative analysis of the sensitivity of UHF sensor positions on a 420 kV power transformer based on electromagnetic simulation
    (2019) Beura, Chandra Prakash; Beltle, Michael; Tenbohlen, Stefan; Siegel, Martin
    With an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions may lead to a decrease in sensitivity to the UHF signals. In this contribution, a previously validated simulation model of a three-phase 300 MVA, 420 kV power transformer is used to perform a sensitivity analysis to determine the most sensitive sensor positions on the tank wall when PD activity occurs inside the windings. A matrix of UHF sensors located on the transformer tank is used to perform the sensitivity analysis. Some of the windings are designed as layer windings, thus preventing the UHF signals from traveling through them and creating a realistic situation with very indirect propagation from source to sensor. Based on these findings, sensor configurations optimized for UHF signal sensitivity, which is also required for PD source localization, are recommended for localization purposes. Additionally, the propagation and attenuation of the UHF signals inside the windings and the tank are discussed in both oil and air.
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    A comprehensive analysis of windings electrical and mechanical faults using a high-frequency model
    (2019) Tahir, Mehran; Tenbohlen, Stefan
    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.