05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access 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, MartinWith 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.Item Open Access Frequency range of UHF PD measurements in power transformers(2023) Tenbohlen, Stefan; Beura, Chandra Prakash; Sikorski, Wojciech; Albarracín Sánchez, Ricardo; Albuquerque de Castro, Bruno; Beltle, Michael; Fehlmann, Pascal; Judd, Martin; Werner, Falk; Siegel, MartinAlthough partial discharge (PD) measurement is a well-accepted technology to assess the quality of the insulation system of power transformers, there are still uncertainties about which frequency range PDs radiate and which frequency range should be evaluated in a measurement. This paper discusses both a UHF PD frequency range obtained from studies investigating laboratory experiments and a frequency range from numerous practical use cases with online and on-site measurements. The literature review reveals a frequency spectrum of ultrahigh-frequency (UHF) PD measurements in the range of 200 MHz to 1 GHz for most publications. Newer publications extend this range from 3 to 6 GHz. The use cases present UHF PD measurements at transformers with power ratings up to 1000 MVA to determine frequency ranges which are considered effective for practical applications. The “common” frequency range, where measurements from all use cases provide signal power, is from approximately 400 MHz to 900 MHz, but it is noted that the individual frequency range, as well as the peak UHF signal power, strongly varies from case to case. We conclude from the discussed laboratory experiments and practical observations that UHF PD measurements in power transformers using either valve or window antennas, according to Cigré, are feasible methods to detect PD.Item Open Access Assessment of overload capabilities of power transformers by thermal modelling(2011) Schmidt, Nicolas; Tenbohlen, Stefan; Skrzypek, Raimund; Dolata, BartekThis contribution presents an approach to determine the overload capabilities of oil-cooled power transformers depending on the ambient temperature. For this purpose the investigated method introduces a simplified, empirical based thermal model that predicts changes in oil temperature with high accuracy. This model considers the entire transformer as a single, homogenous tempered body with a certain thermal capacity. All electrical losses are perceived as an input of equally distributed heat and assumed to be the sum of the load and no-load losses given by the transformer design. In contrary to earlier approaches the heat exchange with the ambience is modelled as a complex function depending first of all on the temperature difference between the transformer and its surroundings. Furthermore, the loading rate, material properties, levels of temperatures and emerging temperature gradients are taken into account as influencing factors determining the heat exchange. To display the behaviour of a specific transformer, the model employs several empirical factors. For determination of these empirical factors an evaluation time of two to four representative weeks of transformer operation is found to be sufficient. To validate the created model and test its operational reliability, measuring data from several ONAN- and ONAF-transformers are consulted. These data sets comprise the top oil and ambient temperature as well as the loading rate and the status of the cooling system. Furthermore, the corresponding name plate data is integrated. Subsequently to the calculation of the top oil temperature, the maximum constant loading rate resulting in a hot-spot temperature below critical level is determined based upon the remarks of IEC 60076 - 7 [1]. Finally, a characteristic linear function for each investigated transformer displaying the maximum loading rate depending solely on the ambient temperature is derived. In case of the investigated ONAN- and ONAF-transformers within a power range of 31.5 - 63 MVA, significant overload potentials could be disclosed.Item Open Access Water saturation limits and moisture equilibrium curves of alternative insulation systems(2011) Tenbohlen, Stefan; Jovalekic, Mark; Bates, Lisa; Szewczyk, RadoslawA method developed for establishing moisture equilibrium curves for any combination of liquid and solid insulation is presented in this paper. Moisture saturation curves for natural and synthetic esters have been presented in the temperature range up to 140°C together with curve for mineral oil as a reference. Sorption isotherms have been established for cellulose based and aramid fiber based materials. Eventually, the moisture equilibrium diagrams have been created for given combinations of solids and liquids. Moisture equilibrium curves have been created for combinations of mineral oil and ester fluids with aramid fiber based papers and boards, as they are commonly used in alternative insulation systems. The new curves give information on moisture distribution within the alternative insulation systems and may be critical for setting the material choices, design rules and maintenance guidelines for equipment using these combinations. Only then the materials could be used optimally and their specific characteristics could bring full range of benefits to the equipment. Also the condition monitoring and diagnostics for the purpose of asset management will be more reliable when these new characteristics are used. It has been observed that insulation components made of aramid insulation may have lower water content comparing to cellulose based conventional materials at the same water content measured in dielectric liquid. As a result, the performance of aramid insulation components may be less sensitive to moisture in oil (aging processes, dielectric strength, partial discharge performance) comparing to conventional systems based on cellulose.Item Open Access Assessment of UHF frequency range for failure classification in power transformers(2024) Schiewaldt, Karl; de Castro, Bruno Albuquerque; Ardila-Rey, Jorge Alfredo; Franchin, Marcelo Nicoletti; Andreoli, André Luiz; Tenbohlen, StefanUltrahigh-frequency (UHF) sensing is one of the most promising techniques for assessing the quality of power transformer insulation systems due to its capability to identify failures like partial discharges (PDs) by detecting the emitted UHF signals. However, there are still uncertainties regarding the frequency range that should be evaluated in measurements. For example, most publications have stated that UHF emissions range up to 3 GHz. However, a Cigré brochure revealed that the optimal spectrum is between 100 MHz and 1 GHz, and more recently, a study indicated that the optimal frequency range is between 400 MHz and 900 MHz. Since different faults require different maintenance actions, both science and industry have been developing systems that allow for failure-type identification. Hence, it is important to note that bandwidth reduction may impair classification systems, especially those that are frequency-based. This article combines three operational conditions of a power transformer (healthy state, electric arc failure, and partial discharges on bushing) with three different self-organized maps to carry out failure classification: the chromatic technique (CT), principal component analysis (PCA), and the shape analysis clustering technique (SACT). For each case, the frequency content of UHF signals was selected at three frequency bands: the full spectrum, Cigré brochure range, and between 400 MHz and 900 MHz. Therefore, the contributions of this work are to assess how spectrum band limitation may alter failure classification and to evaluate the effectiveness of signal processing methodologies based on the frequency content of UHF signals. Additionally, an advantage of this work is that it does not rely on training as is the case for some machine learning-based methods. The results indicate that the reduced frequency range was not a limiting factor for classifying the state of the operation condition of the power transformer. Therefore, there is the possibility of using lower frequency ranges, such as from 400 MHz to 900 MHz, contributing to the development of less costly data acquisition systems. Additionally, PCA was found to be the most promising technique despite the reduction in frequency band information.Item Open Access Transformer winding fault classification and condition assessment based on random forest using FRA(2023) Tahir, Mehran; Tenbohlen, StefanAt present, the condition assessment of transformer winding based on frequency response analysis (FRA) measurements demands skilled personnel. Despite many research efforts in the last decade, there is still no definitive methodology for the interpretation and condition assessment of transformer winding based on FRA results, and this is a major challenge for the industrial application of the FRA method. To overcome this challenge, this paper proposes a transformer condition assessment (TCA) algorithm, which is based on numerical indices, and a supervised machine learning technique to develop a method for the automatic interpretation of FRA results. For this purpose, random forest (RF) classifiers were developed for the first time to identify the condition of transformer winding and classify different faults in the transformer windings. Mainly, six common states of the transformer were classified in this research, i.e., healthy transformer, healthy transformer with saturated core, mechanically damaged winding, short-circuited winding, open-circuited winding, and repeatability issues. In this research, the data from 139 FRA measurements performed in more than 80 power transformers were used. The database belongs to the transformers having different ratings, sizes, designs, and manufacturers. The results reveal that the proposed TCA algorithm can effectively assess the transformer winding condition with up to 93% accuracy without much human intervention.