Multi-Winding Power Transformer Modeling for Fast-Front Transients

Journal Article (2025)
Author(s)

F. Nasirpour (TU Delft - Intelligent Electrical Power Grids)

T. Luo (TU Delft - High Voltage Technology Group)

Mohamad Gaffarian Ghaffarian Niasar (TU Delft - High Voltage Technology Group)

Marjan Popov (TU Delft - Intelligent Electrical Power Grids)

Research Group
Intelligent Electrical Power Grids
DOI related publication
https://doi.org/10.1109/TPWRD.2025.3535419
More Info
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Publication Year
2025
Language
English
Research Group
Intelligent Electrical Power Grids
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
2
Volume number
40
Pages (from-to)
1054-1066
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Abstract

This paper presents a comprehensive model for power transformers, by considering eddy current losses in both the core and conductors. This is achieved through a meticulous analytical approach that ensures high fidelity in representing the transformer's electromagnetic properties. The consideration of magnetic flux effects on inductance and resistance values significantly enhances the model's accuracy and validity. Traditional analytical methods often resort to simplified approaches due to the complexity of these calculations. The paper addresses these limitations by evaluating the eddy current losses in the core and conductors, and by providing a detailed understanding of each component's impact on transformer behavior. Furthermore, by considering the core and conductor effects on the magnetic field distribution, the model handles a wide range of frequencies, making it suitable for conducting comprehensive transient analysis. To validate the model, comparisons with the finite element method and empirical measurements are conducted. Additionally, a reduced-order transformer model is developed using admittance matrix reduction. This approach focuses on the nodes of interest, effectively eliminating not-observed nodes and reducing computational complexity without compromising accuracy. In this way, voltages at specific points of interest are computed efficiently, maintaining the accuracy of the original model.

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