Research on short-circuit fault identification method of traction transformer

The short-circuit fault of traction transformer is very harmful. Aiming at the limitation of the existing second harmonic blocking principle, a differential protection algorithm of traction transformer based on fractal correlation dimension is proposed. The algorithm is sensitive to the important parameters of the nonlinear dynamic evolution characteristics of the transformer. The inrush current and the short-circuit fault current are effectively identified by the different fault dimension eigenvalues of the transformer under different working conditions. The simulation model of $V / x$ traction transformer and fractal protection algorithm is built, and the accuracy of the method is verified by uploading it to the real-time digital simulation platform RT-plus.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/icemce64157.2024.10862055
Primary Topic
Power Systems and Technologies
Type
article
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Research on short-circuit fault identification method of traction transformer

Menghao Zhang, Kai Sun, Bin Ma, Yang Liu et al.
Power Systems and Technologies
article

Research on short-circuit fault identification method of traction transformer

Menghao Zhang, Kai Sun, Bin Ma, Yang Liu, Ji Cheng, D. Ao, Qifei Zhu, Xingjun Tian
article en

Abstract

The short-circuit fault of traction transformer is very harmful. Aiming at the limitation of the existing second harmonic blocking principle, a differential protection algorithm of traction transformer based on fractal correlation dimension is proposed. The algorithm is sensitive to the important parameters of the nonlinear dynamic evolution characteristics of the transformer. The inrush current and the short-circuit fault current are effectively identified by the different fault dimension eigenvalues of the transformer under different working conditions. The simulation model of $V / x$ traction transformer and fractal protection algorithm is built, and the accuracy of the method is verified by uploading it to the real-time digital simulation platform RT-plus.

Shijiazhuang Tiedao University (CN)
Openalex Percentile: Top 75%
Power Systems and Technologies
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