05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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Author: search.filters.author.Tenbohlen, Stefan

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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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    Compatibility study of silicone rubber and mineral oil
    (2021) Karambar, Smitha; Tenbohlen, Stefan
    In this study, three types of silicone rubbers, namely, insulative silicone rubber, conductive silicone rubber and silicone rubber with conductive as well as insulative layers are investigated for their compatibility with mineral oil. Mineral oil with different silicone rubber samples is thermally aged at 130 °C for 360 h, 720 h and 1080 h and at 23 °C, 98 °C and 130 °C for 360 h. At the end of each ageing interval, mineral oil and oil-impregnated silicone rubbers are investigated for their dielectric properties. Aged mineral oil samples are investigated for their moisture content, breakdown voltage, colour number, dissolved gases and total acid number, whereas solid insulation samples are investigated for their moisture content. Additionally, pressboard samples in mineral oil and mineral oil without any solid insulation materials are also aged under the same conditions and are investigated for their dielectric properties. From the obtained results, it can be assessed that the presence of carbon particles in conductive silicone rubber negatively impacts the dielectric properties of mineral oil. Among the investigated silicone rubbers, the insulative silicone rubber exhibits good compatibility with mineral oil and a strong potential for being used in mineral oil.
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    Einfluss der Abschlussimpedanz von Hochvoltkabeln auf Funkstörgrößen in elektrisch angetriebenen Kraftfahrzeugen
    (2012) Reuter, Martin; Waible, Manuel; Tenbohlen, Stefan; Köhler, Wolfgang
    In diesem Beitrag wird die Frage untersucht, welche Auswirkung die Fehlanpassung von Kfz-Hochvoltkabeln auf EMV-Störgrößen in der Komponentenmessung nach CISPR 25 hat.
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    Transformer winding condition assessment using feedforward artificial neural network and frequency response measurements
    (2021) Tahir, Mehran; Tenbohlen, Stefan
    Frequency response analysis (FRA) is a well-known method to assess the mechanical integrity of the active parts of the power transformer. The measurement procedures of FRA are standardized as described in the IEEE and IEC standards. However, the interpretation of FRA results is far from reaching an accepted and definitive methodology as there is no reliable code available in the standard. As a contribution to this necessity, this paper presents an intelligent fault detection and classification algorithm using FRA results. The algorithm is based on a multilayer, feedforward, backpropagation artificial neural network (ANN). First, the adaptive frequency division algorithm is developed and various numerical indicators are used to quantify the differences between FRA traces and obtain feature sets for ANN. Finally, the classification model of ANN is developed to detect and classify different transformer conditions, i.e., healthy windings, healthy windings with saturated core, mechanical deformations, electrical faults, and reproducibility issues due to different test conditions. The database used in this study consists of FRA measurements from 80 power transformers of different designs, ratings, and different manufacturers. The results obtained give evidence of the effectiveness of the proposed classification model for power transformer fault diagnosis using FRA.
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    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, Martin
    Although 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.
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    Classification of superimposed partial discharge patterns
    (2021) Adam, Benjamin; Tenbohlen, Stefan
    Phase resolved partial discharge patterns (PRPD) are routinely used to assess the condition of power transformers. In the past, classification systems have been developed in order to automate the fault identification task. Most of those systems work with the assumption that only one source is active. In reality, however, multiple PD sources can be active at the same time. Hence, PRPD patterns can overlap and cannot be separated easily, e.g., by visual inspection. Multiple PD sources in a single PRPD represent a multi-label classification problem. We present a system based on long short-term memory (LSTM) neural networks to resolve this task. The system is generally able to classify multiple overlapping PRPD by while only being trained by single class PD sources. The system achieves a single class accuracy of 99% and a mean multi-label accuracy of 43% for an imbalanced dataset. This method can be used with overlapping PRPD patterns to identify the main PD source and, depending on the data, also classify the second source. The method works with conventional electrical measuring devices. Within a detailed discussion of the presented approach, both its benefits but also its problems regarding different repetition rates of different PD sources are being evaluated.
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    New mitigation methods for transient overvoltages in gas insulated substations
    (2012) Burow, Simon; Riechert, Uwe; Köhler, Wolfgang; Tenbohlen, Stefan
    During switching of disconnectors (DS) in GIS a varying number of pre-strikes and re-strikes occur. Due to the very short duration of the voltage collapse, traveling surges are generated in the busbar duct. These very fast transient overvoltages (VFTO) can become the limiting dielectric stress which defines the dimensions at UHV voltage levels. The decision shall be based on the maximum VFTO peak value that occurs with reference to the rated lightning impulse withstand voltage (LIWV) of the equipment. If the maximum VFTO is higher than the LIWV, it is necessary to consider the VFTO level as dimensioning criteria or to suppress VFTO by suitable measures. The main challenges are the reduction in VFTO amplitudes and finally the reduction of the effects of VFTO on the equipment. For the different sources of VFTO and for the different equipment different mitigation methods are known. The damping of VFTO by integration of a damping resistor is a well proven technology. The way to overcome the drawback of such unwieldy designs is to use other internal damping measures. Several methods have been proposed and examined in the past, such as ferrite material or high frequency (RF) resonators. The VFTO damping solution utilizing ferrite rings has been analysed and tested and will be described here. The measurements show that a damping effect can be achieved, but with an important drawback: the magnetic material goes easily into saturation, which complicates the design and reduces its general applicability and robustness. A new approach for damping is to implement compact electromagnetic high-frequency resonators with low quality factor specially designed to cover a wider frequency range. The novelty of this idea is not only to design the resonators but also to dissipate the VFTO energy. The VFTO damping effect of the developed RF resonator tuned to the dominant harmonic component was confirmed by experiments. Rings of a nanocrystalline alloy placed around the GIS conductor were also investigated. Depending on number, material and size of the rings a good mitigation could be achieved.
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    Black-box modeling for investigating internal resonances in high-voltage windings of dry-type transformers
    (2025) Probst, Felipe L.; Tenbohlen, Stefan
    Understanding internal resonance phenomena in transformer windings is essential for evaluating insulation performance and preventing equipment failure under transient conditions. This study presents a measurement-based modeling approach to assess internal voltage distributions in a high-voltage transformer winding of a dry-type distribution transformer. Frequency-domain admittance and voltage transfer functions were experimentally obtained and approximated using vector fitting. The resulting models were employed to simulate time-domain responses through a two-step procedure that integrates electromagnetic transient simulations of the terminal circuit with frequency-derived internal voltage models. The validation was performed using a sinusoidal excitation at 51 kHz, corresponding to the first-mode resonance frequency. Simulated internal voltages and input currents showed close agreement with experimental measurements, confirming the model’s accuracy. The study identified two critical resonance frequencies at 51 kHz and 59 kHz, at which voltage amplification can become severe. At 51 kHz, the maximum overvoltage reached nearly seven times the applied voltage at the winding midpoint, indicating a substantial risk of dielectric failure. These findings highlight the importance of accurately characterizing internal resonances in transformer windings, especially during insulation coordination studies. The proposed methodology offers an effective tool for analyzing internal overvoltages and contributes to the development of more robust transformer design and protection strategies.
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    Assessment of overload capabilities of power transformers by thermal modelling
    (2011) Schmidt, Nicolas; Tenbohlen, Stefan; Skrzypek, Raimund; Dolata, Bartek
    This 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.
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    Application of pathfinding algorithms in partial discharge localization in power transformers
    (2024) Beura, Chandra Prakash; Wolters, Jorim; Tenbohlen, Stefan
    The introduction of artificial intelligence (AI) to ultra-high-frequency (UHF) partial discharge (PD) monitoring systems in power transformers for the localization of PD sources can help create a robust and reliable system with high usability and precision. However, training the AI with experimental data or data from electromagnetic simulation is costly and time-consuming. Furthermore, electromagnetic simulations often calculate more data than needed, whereas, for localization, the signal time-of-flight information is the most important. A tailored pathfinding algorithm can bypass the time-consuming and computationally expensive process of simulating or collecting data from experiments and be used to create the necessary training data for an AI-based monitoring system of partial discharges in power transformers. In this contribution, Dijkstra’s algorithm is used with additional line-of-sight propagation algorithms to determine the paths of the electromagnetic waves generated by PD sources in a three-dimensional (3D) computer-aided design (CAD) model of a 300 MVA power transformer. The time-of-flight information is compared with results from experiments and electromagnetic simulations, and it is found that the algorithm maintains accuracy similar to that of the electromagnetic simulation software, with some under/overestimations in specific scenarios, while being much faster at calculations.