power transformer
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Vladimir Mikhailovich Levin ◽  
Ammar Abdulazez Yahya ◽  
Diana A. Boyarova

Power transformers are one of the most important and complex parts of an electric power system. Maintenance is performed for this responsible part based on the technical condition of the transformer using a predictive approach. The technical condition of the power transformer can be diagnosed using a range of different diagnostic methods, for example, analysis of dissolved gases (DGA), partial discharge monitoring, vibration monitoring, and moisture monitoring. In this paper, the authors present a digital model for predicting the technical condition of a power transformer and determining the type of defect and its cause in the event of defect detection. The predictive digital model is developed using the programming environment in LabVIEW and is based on the fuzzy logic approach to the DGA method, interpreted by the key gas method and the Dornenburg ratio method. The developed digital model is verified on a set of 110 kV and 220 kV transformers of one of the sections of the distribution network and thermal power plant in the Russian Federation. The results obtained showed its high efficiency in predicting faults and the possibility of using it as an effective computing tool to facilitate the work of the operating personnel of power enterprises.

Michal Stebel ◽  
Krzysztof Kubiczek ◽  
Gustavo Rios Rodriguez ◽  
Michal Palacz ◽  
Luciano Garelli ◽  

Milos Bjelić ◽  
Bogdan Brković ◽  
Mileta Žarković ◽  
Tatjana Miljković

Mengmeng Ai ◽  
Wenhui Liu ◽  
Yi Shan

In the process of Ultra high voltage direct current (UHVDC) transmission, the direct current (DC) bias of power transformer is easily induced, which makes the transformer exciting current distorted, the ferromagnetic material saturated and the magnetic leakage increased, and then leads to the increase of core vibration and noise. Aiming at this problem, taking a 240 MVA, 330 kV three-phase five-column power transformer as an example, the coupling of the electromagnetic field, structural force field and acoustic field is studied, and the influence of DC bias on vibration and noise of power transformer core is analyzed in this paper. According to the magnetic density and electric density of transformer core under different magnetic bias degree, the structural force field is solved, and the displacement and surface acceleration of core are obtained, which can be as the excitation of sound field to determine the noise distribution of transformer. In order to avoid the natural frequencies which easily cause resonance, the modal analysis is needed to obtain the natural frequencies and modal modes of the core. The transformer noise under no-load and DC bias conditions of the prototype is tested experimentally and compared with the theoretical calculation, the results prove the accuracy of the simulation calculation method in this paper.

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