Compensating algorithm suitable for use with measurement-type current transformers for protection

Kang, Yong-Cheol; Lim, Ui-Jai; Kang, Sang-Hee

doi:10.1049/ip-gtd:20045115

Cited by 12 publications

(7 citation statements)

References 6 publications

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“…Two methods have become the most common for solving the CT saturation problem: saturation detection with subsequent restoration of distorted current values [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and saturation detection with subsequent blocking of the PS and EA algorithms [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41].…”

Section: Review Of the Ct Saturation Detection And Compensation Methodsmentioning

confidence: 99%

Detection of Current Transformer Saturation Based on Machine Learning

Odinaev,

Pazderin,

Safaraliev

et al. 2024

Mathematics

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One of the tasks in the operation of electric power systems is the correct functioning of the protection system and emergency automation algorithms. Instrument voltage and current transformers, operating in accordance with the laws of electromagnetism, are most often used for information support of the protection system and emergency automation algorithms. Magnetic core saturation of the specified current transformers can occur during faults. As a result, the correct functioning of the protection system and emergency automation algorithms is compromised. The consequences of current transformers saturation are mostly reflected in the main protections of network elements operating on a differential principle. This work aims to consider the analysis of current transformer saturation detection methods. The problem of identifying current transformer saturation is reduced to binary classification, and methods for solving the problem based on artificial neural networks, support vector machine, and decision tree algorithms are proposed. Computational experiments were performed, and their results were analyzed with imbalanced (dominance of the number of current transformer saturation modes over the number of modes with its normal operation) and balanced classes 0 (no current transformer saturation) and 1 (current transformer saturation).

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Section: Review Of the Ct Saturation Detection And Compensation Methodsmentioning

confidence: 99%

Detection of Current Transformer Saturation Based on Machine Learning

Odinaev,

Pazderin,

Safaraliev

et al. 2024

Mathematics

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“…The duration of the CT saturation depends on the time constant of the decaying DC offset. Besides, the start as well as the degree of CT saturation also depends on remanent flux of CT core . Therefore, for the second evaluation case, we focus on the impact of uncertainty of those three factors: amplitude and time constant of the decaying DC offset ( x 1 , x 2 ), which have been previously described; and remanent flux ( x 6 ).…”

Section: Nuisance Components and Uncertain Factorsmentioning

confidence: 99%

A novel global sensitivity analysis approach in testing measurement algorithms used by protective relays

Ibrahim

Živanović

2012

Int. Trans. Electr. Energ. Syst.

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SUMMARY Measurement algorithm is the important element of Intelligent Electronic Devices (IEDs) used in protection and monitoring of transmission and distribution networks. The function of the measurement algorithm is to estimate fundamental frequency component (phasor) of current and voltage signals recorded during network faults. The estimated fundamental component is used by variety of protection algorithms for the successful operation of the IEDs. The most popular measurement algorithm is the Discrete Fourier Transform (DFT). However, the estimation of the fundamental frequency component by the DFT algorithm will produce error if input signal contains nuisance components such as a decaying DC offset. This paper evaluates the performance of DFT measurement algorithm when its input signal is influenced by variety of the nuisance components. Various random factors will impact the amount of nuisance components present in a measured signal. Therefore, we propose a novel global uncertainty and sensitivity analysis technique to determine in a systematic way the impact of nuisance components on the performance of measurement algorithms. In addition to the full‐cycle DFT, we analyze performance of half‐cycle DFT and full‐cycle cosine filter algorithms. Impact of nuisance components due to current transformer (CT) saturation and without saturation was studied. Steady‐state and transient performance indices are defined to evaluate the performance of the algorithms. Copyright © 2012 John Wiley & Sons, Ltd.

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“…Within the second approach, in order to compensate for an error in the CT in its saturation mode or to exclude the influence of saturation on the operation of RPS, saturation detection [4][5][6][7][8][9][10] and compensation methods [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] are used. The latter, due to the complexity of adaptation to real conditions, have not found wide practical development.…”

Section: Introductionmentioning

confidence: 99%

“…Selection and filtering are the most important of all three listed subtasks. With reservations, one can say that the methods proposed within the second approach are designed to solve the problem of selection [4][5][6][7][8][9][10] and filtration [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Mathematical Methods for Compensating a Current Signal under Current Transformers Saturation Conditions

Odinaev

Gulakhmadov

Murzin

et al. 2021

Sensors

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Current measurements from electromagnetic current transformers are essential for the construction of secondary circuit systems, including for protection systems. Magnetic core of these transformers are at risk of saturation, as a result of which maloperation of protection algorithms can possibly occur. The paper considers methods for recovering a current signal in the saturation mode of current transformers. The advantages and disadvantages of methods for detecting the occurrence of current transformers core saturation are described. A comparative analysis of mathematical methods for recovering a current signal is given, their approbation was carried out, and the most promising of them was revealed. The stability and sensitivity of recovery methods were tested by adding white noise to the measured signal and taking into account the initial flux density (remanent magnetization) in the current transformers core. Their comparison is given on the basis of angular, magnitude, and total errors at a given simulation interval.

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Compensating algorithm suitable for use with measurement-type current transformers for protection

Cited by 12 publications

References 6 publications

Detection of Current Transformer Saturation Based on Machine Learning

Detection of Current Transformer Saturation Based on Machine Learning

A novel global sensitivity analysis approach in testing measurement algorithms used by protective relays

Comparison of Mathematical Methods for Compensating a Current Signal under Current Transformers Saturation Conditions

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