Development of a new fault zone identification scheme for busbar using logistic regression classifier

Jena, Soumitri; Bhalja, Bhavesh R.

doi:10.1049/iet-gtd.2016.0785

Cited by 17 publications

(15 citation statements)

References 22 publications

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“…Some other approaches related to regression models include Poisson regression, least-square regression, and logistic regression [70]. Publications such as Jena and Bhalja [71] use a logistic regression binary classifier for the development of a new fault zone identification scheme for busbar verified by modeling an existing power generation station in a design software package. The proposed scheme is able to identify the fault zone with an accuracy of 99% when it is tested on a large dataset (28,800) by using a small training dataset (9600 cases).…”

Section: Regression-based Methodsmentioning

confidence: 99%

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

et al. 2020

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Data mining is a technological and scientific field that, over the years, has been gaining more importance in many areas, attracting scientists, developers, and researchers around the world. The reason for this enthusiasm derives from the remarkable benefits of its usefulness, such as the exploitation of large databases and the use of the information extracted from them in an intelligent way through the analysis and discovery of knowledge. This document provides a review of the predictive data mining techniques used for the diagnosis and detection of faults in electric equipment, which constitutes the pillar of any industrialized country. Starting from the year 2000 to the present, a revision of the methods used in the tasks of classification and regression for the diagnosis of electric equipment is carried out. Current research on data mining techniques is also listed and discussed according to the results obtained by different authors.

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Section: Regression-based Methodsmentioning

confidence: 99%

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

et al. 2020

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“…When taking such cases into account, the AbI of bad data turns to be a multi-class classification problem. There are many classifiers which could produce probability estimates of each class rather than the prediction of a single class, such as logistic regression [23], decision tree classifier [24], and BC [14]. The logistic regression models, which are more suitable for two-class classification, perform less well than BCs in multi-class classification; the decision trees fragment the training set into smaller pieces, which inevitably yield less reliable probability estimates, in addition, they suffer from the replicated subtree problem [25].…”

Section: Bc Training and Classificationmentioning

confidence: 99%

Abductive identification of bad data: methodology and field test

Sheng

Sun

et al. 2017

IET Generation, Transmission & Distribution

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“…Hence, protection zone selection must be highly discriminative, such that a busbar protective relay operates only for a protection zone of BB fault [4]. In addition, slow fault clearing results in extensive damage at the fault location as a consequence of the high concentration of short circuit current at busbar station [5]. Also, high through‐fault current may lead to Current Transformer (CT) saturation problem.…”

Section: Introductionmentioning

confidence: 99%

“…However, there is always a need to develop innovative and efficient methods of busbar protection. References [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] present some modern techniques, which utilize sophisticated algorithms, to provide fast busbar protection and reliable performance during CT saturation. Some busbar protections based on Travelling Wave (TW), which used the transient fault information to avoid CT saturation effects and improve the speed and sensitivity of the protective relay [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Integrated busbar protection scheme utilizing a numerical technique based on coherence method

Mahmoud

2021

The Journal of Engineering

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A Busbar (BB) is one of the most important elements of a power system, which links a variety of elements such as generators, power transformers, transmission lines and loads. The BB fault current magnitude is very large, which has to be immediately cleared in order to minimize the failure in the power system, and to avoid the CT saturation effects. This paper presents a novel BB protection scheme based on closed‐tripping characteristics of coherence coefficients computed for BB current signals. Three‐phase current signals of each circuit connected to the protected busbar are measured for calculating nine cross‐coherence coefficients. These coefficients are compared with each other and with a pre‐determined threshold value to identify the fault location, classification and direction discrimination, as well as to differentiate the internal and external faults with CT saturation extent. The scheme is tested under different types of external and internal faults with variations of faulty phase(s), fault locations, fault resistances, fault inception angles, and power flow angles. ATP platform is used for power system simulation, and MATLAB software is applied to validate the proposed protection algorithm. The simulation results prove that the scheme is fast, where its operating time is within a sub‐cycle time range, and it has the ability to discriminate between internal and external faults with/without CT saturation condition. Moreover, the numerical technique is immune to CT saturation effect, and it is simple, effective, secure, reliable, stable and feasible.

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Development of a new fault zone identification scheme for busbar using logistic regression classifier

Cited by 17 publications

References 22 publications

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

Abductive identification of bad data: methodology and field test

Integrated busbar protection scheme utilizing a numerical technique based on coherence method

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