05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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

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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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    Power quality mitigation via smart demand-side management based on a genetic algorithm
    (2022) Eisenmann, Adrian; Streubel, Tim; Rudion, Krzysztof
    In modern electrical grids, the number of nonlinear grid elements and actively controlled loads is rising. Maintaining the power quality will therefore become a challenging task. This paper presents a power quality mitigation method via smart demand-side management. The mitigation method is based on a genetic algorithm guided optimization for smart operational planning of the grid elements. The algorithm inherits the possibility to solve multiple, even competing, objectives. The objective function uses and translates the fitness functions of the genetic algorithm into a minimization or maximization problem, thus narrowing down the complexity of the addressed high cardinality optimization problem. The NSGA-II algorithm is used to obtain feasible solutions for the auto optimization of the demand-side management. A simplified industrial grid with five different machines is used as a case study to showcase the minimization of the harmonic distortion to normative limits for all time steps during a day at a specific grid node, while maintaining the productivity of the underlying industrial process.
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    Optimized planning of distribution grids considering grid expansion, battery systems and dynamic curtailment
    (2021) Laribi, Ouafa; Rudion, Krzysztof
    The increasing integration of renewable energies into the grid is calling for the expansion of the power transport capacities in the distribution system. Yet, the expansion of the grid could require long authorization procedures and cannot be always asserted. Therefore, a higher utilization of the existing grid is becoming increasingly necessary today. This paper proposes a new time series-based planning method for distribution systems using classical grid expansion instruments as well as innovative planning instruments such as battery storage systems (BSS) and dynamic power curtailment (DPC). These planning instruments could be applied individually or combined. The aim of the BSS and DPC application is to enable a higher utilization of the grid at minimal costs. The proposed method, which has been implemented as an automated planning algorithm, determines the cost optimal grid reinforcement measures that ensure the prevention of prognosticated congestions in the considered grid. Furthermore, the application of the proposed planningmethod on the considered power system has proven that a combination of BSS and grid expansion could be more economical than an individual application of BSS and grid expansion.
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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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    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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    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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    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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    Identification of grid impedance by broadband signals in power systems with high harmonics
    (2021) Buchner, Matthias; Rudion, Krzysztof
    Grid impedance is an important parameter and is used to perform impedance-based stability analysis for the operation of grid-connected systems, such as power electronics-interfaced solar, wind and other distributed power generation systems. The identification of grid impedance with the help of broadband signals is a popular method, but its robustness depends strongly on the harmonic disturbances caused by non-linear loads or power electronics. This paper provides an in-depth analysis of how harmonics affect the identification of grid impedance while using broadband measurements. Furthermore, a compensation method is proposed to remove the disturbing influences of harmonics on broadband impedance identification. This method is based on exploiting the properties of the used maximum-length binary sequence (MLBS). To explain the methodology of the proposed method, the design basis for the excitation signal is discussed in detail. The analysis from simulations and a real measurement in an industrial power grid shows the effectiveness of the proposed method in compensating the disturbing influences of harmonics on broadband impedance measurements.
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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.