A frequency curves analysis-based method for transformers differential protection

Fani, Bahador; Golshan, Mohammad; Saghaian-nejad, M.

doi:10.1002/etep.491

Cited by 2 publications

(2 citation statements)

References 25 publications

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“…Currently, there are three main approaches to identifying the excitation inrush and fault currents. One is the current aspect [2][3][4] . Literature [5] uses the features of asymmetric and rapidly decaying excitation inrush current waveform, and Literature [6] uses the non-continuous elements of the excitation inrush current for identification.…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Identification of Magnetizing Inrush Current based on Empirical Modal Decomposition

Duan

Zhang

et al. 2023

J. Phys.: Conf. Ser.

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The accurate identification of the converter transformer magnetizing inrush current can ensure the safety of the operation of the UHV DC transmission system. In the differential protection of the converter transformer, it is extremely hard to distinguish between the excitation inrush current generated when the transformer is closed and the Fault current due to internal fault, which leads to frequent misoperation of the transformer protection to the extent that the transformer access fails. This paper proposes a current identification model based on empirical modal decomposition (EMD) and probabilistic neural network (PNN) algorithm with particle swarm (PSO) optimization. The EMD algorithm decomposes the current waveform, and the eigenmode functions (IMFs) of the three highest correlation bars are selected. The energy, cliffs, and standard deviation of the IMFs are extracted as the original waveform eigenvectors.

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Section: Introductionmentioning

confidence: 99%

Research on Intelligent Identification of Magnetizing Inrush Current based on Empirical Modal Decomposition

Duan

Zhang

et al. 2023

J. Phys.: Conf. Ser.

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“…Setting a threshold and requirement of both current and voltage signals simultaneously are the weak points of this method. Also, in , a frequency curves analysis‐based method for transformers differential protection, but operation time of this method is long because of calculation the frequency curves. Also , a technique for discrimination between inrush current and internal faults based on discrete wavelet transform is presented, and in , a runs test‐based method for discrimination between internal faults and inrush currents is introduced.…”

Section: Introductionmentioning

confidence: 99%

A novel technique for internal fault detection of power transformers based on moving windows

Abniki

Sanaye‐Pasand

2013

Int. Trans. Electr. Energ. Syst.

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SUMMARY Power transformer differential relays may incorrectly operate due to inrush condition or transformer external faults lead to current transformer (CT) saturation. In this paper, a new technique is presented to distinguish internal fault current from magnetizing inrush current in power transformers. The proposed technique applies two moving windows which both of them estimate magnitude of transformer differential current using different methods. The first moving window method is based on full‐cycle Fourier algorithm (long window) which uses one cycle samples of the current and provides precise estimation. The second one is originated from least error square (LES) method that has five sample point input data (short window). LES method has fast response, but its estimation might not be quite accurate. The proposed technique (which is a combination of two mentioned methods) presents a new criterion for discrimination between internal fault currents and inrush currents using the differences between output values of these two estimators. Meanwhile, obtained results demonstrate precise operation of the proposed algorithm for different conditions such as CT saturation and over‐flux condition; therefore, it can be a multi‐objective technique for transformer protection. Also, a general scheme is presented in order to improve differential protection. In this paper, a real part of 400/230 kV Iranian national grid is simulated using PSCAD software for evaluating the performance of the proposed algorithm. Also, additional validation of the proposed technique is tested offline using data collected from a three‐phase, 5 kVA, 60 Hz, laboratory prototype transformer. Copyright © 2013 John Wiley & Sons, Ltd.

show abstract

A frequency curves analysis-based method for transformers differential protection

Cited by 2 publications

References 25 publications

Research on Intelligent Identification of Magnetizing Inrush Current based on Empirical Modal Decomposition

Research on Intelligent Identification of Magnetizing Inrush Current based on Empirical Modal Decomposition

A novel technique for internal fault detection of power transformers based on moving windows

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