A Decision-Tree-Based Method for Fault Classification in Single-Circuit Transmission Lines

Jamehbozorg, Arash; Shahrtash, S. Mohammad

doi:10.1109/tpwrd.2010.2053222

Cited by 120 publications

(46 citation statements)

References 11 publications

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“…Traditionally, these techniques apply direct analysis over symmetrical components [20] or use spectral analysis (such as FFT [18] or DWT [21]) to extract the fault features. These studies are commonly supported by computational intelligence, such as Artificial Neural Networks (ANNs) [22], Fuzzy Logic (FL) [23], Decision Trees (DTs) [24] or Support Vector Machines (SVMs) [25].…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems

et al. 2016

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Abstract:In the last few decades, the Smart Grid paradigm presence has increased within power systems. These new kinds of networks demand new Operations and Planning approaches, following improvements in the quality of service. In this sense, the role of the Distribution Management System, through its Outage Management System, is essential to guarantee the network reliability. This system is responsible for minimizing the consequences arising from a fault event (or network failure). Obviously, knowing where the fault appears is critical for a good reaction of this system. Therefore, several fault location techniques have been proposed. However, most of them provide individual results, associated with specific testbeds, which make the comparison between them difficult. Due to this, a review of fault location methods has been done in this paper, analyzing them for their use on underground distribution lines. Specifically, this study is focused on an impedance-based method because their requirements are in line with the typical instrumentation deployed in distribution networks. This work is completed with an exhaustive analysis of these methods over a PSCAD TM X4 implementation of the standard IEEE Node Test Feeder, which truly allows us to consistently compare the results of these location methods and to determine the advantages and drawbacks of each of them.

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Section: Introductionmentioning

confidence: 99%

A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems

et al. 2016

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“…Security is a measure of assessing the performance of the proposed differential relaying scheme in case of external fault situations. An interesting observation is made while comparing the performance indices of DT-based relaying [9] with the proposed differential relaying scheme at different fault locations of the studied single circuit transmission line. The feature set considered in [9] includes voltage and current signals of different phases.…”

Section: Performance Assessment and Discussionmentioning

confidence: 99%

“…1, which includes deriving differential features, building DT, transforming DT to fuzzy-DT and final relaying decision. The proposed scheme includes 21 possible differential features which could be mostly affected during the fault process [2, [8][9][10][11]. The differential features considered in the proposed study are as follows: † X 1 = ∂(V s1 − V r1 )/dt: (rate of change of positive sequence voltage difference) † X 2 = ∂(I s1 − I r1 )/dt: (rate of change of positive sequence current difference) † X 3 = ∂(V s2 − V r2 )/dt: (rate of change of negative-sequence voltage difference) † X 4 = ∂(I s2 − I r2 )/dt: (rate of change of negative-sequence current difference)…”

Section: Proposed Relaying Schemementioning

confidence: 99%

Decision tree‐induced fuzzy rule‐based differential relaying for transmission line including unified power flow controller and wind‐farms

Jena

Samantaray

Tripathy

2014

IET Generation, Transmission & Distribution

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The paper presents a decision tree (DT) induced fuzzy rule-based intelligent differential relaying scheme for transmission lines including unified power flow controller (UPFC) and wind-farms. The conventional distance relaying scheme fails miserably in protecting transmission lines including flexible AC transmission systems controllers such as UPFC and further, the protection issues become more challenging when wind-farm is integrated. The proposed protection scheme extracts features from the instantaneous voltage and current signals from both ends of the transmission line using discrete Fourier transform based pre-processor and computes corresponding differential features. The differential features are used to build the fault classification tree using a data-mining algorithm known as DT. Further, the fuzzy membership functions are drawn using the DT thresholds and the corresponding fuzzy rule-base is developed for final relaying decision. The proposed technique has been extensively tested (in MATLAB environment) for single circuit and double circuit transmission lines including UPFC and wind-farms with wide variations in operating conditions. The test results indicate that the proposed DTinduced fuzzy rule-based relaying scheme is highly reliable and robust for protection of complex transmission line including UPFC and wind-farm.

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“…In an effort to overcome the above problems due to system inconstancy and for better performance, several authors explored artificial intelligence applications with fuzzy logic [8,9], artificial neural networks (ANNs) [10,11], support vector machines (SVMs) [12,13], etc., to solve the fault classification problem. The inputs to these knowledge-based methods are mainly either steady-state or transient components of the fault voltage/current signals.…”

Section: Introductionmentioning

confidence: 99%

Transient- and probabilistic neural network-based fault classification in EHV three-terminal lines

Bhupatiraju¹,

Dhanikonda²,

Pulipaka³

2018

Turk J Elec Eng & Comp Sci

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This paper presents a fast and accurate fault classifier for three-terminal transmission circuits. Traditional phasor-based methods fail to meet the high speed requirements of modern power grids and necessitate alternative solutions. The transient-based schemes use advanced signal processing techniques to achieve fast and accurate fault classification. As the three-terminal lines experience very pronounced transients during faults, the proposed method makes use of the fault-generated transients to quickly and correctly classify the fault. Many transient-based schemes fail to give the required accuracy since the transient patterns with relay-measured signals are highly influenced by fault conditions. Therefore, a thorough analysis of transient patterns is carried out in this paper, and based on the typical patterns revealed by the analysis of fault-generated transients an effective classification algorithm is developed. For high-speed classification, only a quarter-cycle of postfault voltage signals measured at the relay points will be processed for feature extraction using wavelet transform. The algorithm includes a hybrid procedure based on a probabilistic neural network for tackling the effects of fault inception angle and fault resistance in transient variations. Particularly, it is designed to overcome the problem with double-line-to-ground fault classification. The technique is simple and extensive simulation studies and comparison substantiate the efficacy of the proposed method under different fault conditions.

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A Decision-Tree-Based Method for Fault Classification in Single-Circuit Transmission Lines

Cited by 120 publications

References 11 publications

A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems

A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems

Decision tree‐induced fuzzy rule‐based differential relaying for transmission line including unified power flow controller and wind‐farms

Transient- and probabilistic neural network-based fault classification in EHV three-terminal lines

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