A network distribution power system fault location based on neural eigenvalue algorithm

Martins, L. Sousa; Martins, J. F.; Alegria, C.M.; Pires, V. Fernão

doi:10.1109/ptc.2003.1304592

Cited by 19 publications

(7 citation statements)

References 8 publications

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“…Calculations for fault detection and location indices were carried out in [40,41]. Researchers used CT with little modifications called Clarke-Concordia transformation [43,44] and Karrenbauer transformation [45], respectively, to expedite the implementation of fault characteristics.…”

Section: Modal Transformationmentioning

confidence: 99%

A Review of Fault Diagnosing Methods in Power Transmission Systems

et al. 2020

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Transient stability is important in power systems. Disturbances like faults need to be segregated to restore transient stability. A comprehensive review of fault diagnosing methods in the power transmission system is presented in this paper. Typically, voltage and current samples are deployed for analysis. Three tasks/topics; fault detection, classification, and location are presented separately to convey a more logical and comprehensive understanding of the concepts. Feature extractions, transformations with dimensionality reduction methods are discussed. Fault classification and location techniques largely use artificial intelligence (AI) and signal processing methods. After the discussion of overall methods and concepts, advancements and future aspects are discussed. Generalized strengths and weaknesses of different AI and machine learning-based algorithms are assessed. A comparison of different fault detection, classification, and location methods is also presented considering features, inputs, complexity, system used and results. This paper may serve as a guideline for the researchers to understand different methods and techniques in this field. transmission system topologies can be minimized by using the interspersed sensors for the collection of voltage and current signals. The second limitation is the lack of computational capability and communication. Synchronized global positioning system (GPS) sampling and high-speed broadband communications for IEDs in power grids are proposed in [8]. These technical advancements assure the quick response to faulty scenarios and the effective functioning of online monitoring mechanisms based on sensor networks. The availability of high-performance computing solutions gives provision to the implementation of higher computation complexity methods [7].Short circuit faults are more likely to appear in power systems (PS) than the series faults, break in the path of current. Shunt faults result in catastrophes and leave hazardous effects on PS. Short circuit faults can be divided into symmetrical and asymmetrical faults and further classification is presented in Figure 1 for the three-phase system [11].

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Section: Modal Transformationmentioning

confidence: 99%

A Review of Fault Diagnosing Methods in Power Transmission Systems

et al. 2020

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“…The two input vectors are eigenvalue and eigenvector data which are obtained through Clarke-Concordia transformation of the fault and pre-fault currents. The proposed method by [25] shows immunity against total harmonic distortion, requires less input (only current components are used) and able to match and locate faults.…”

Section: Intelligence Based Methodsmentioning

confidence: 99%

A Comprehensive Review of Fault Location Methods for Distribution Power System

Gana

Aziz

Ali

et al. 2017

IJEECS

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“…Modal transformations such as Clarke transformation (CT) was used in [39][40][41] to decouple three-phase quantities represented by a, b and c and transform them into components represented by α, β and 0, on the basis of which fault types were characterised by describing the relationships between phase quantities and modal components [41], and fault detection and location indices were calculated [39,40]. Authors in [42,43] adopted a modification of CT called Clarke-Concordia transformation. Karrenbauer transformation, another type of modal transformation, was used in [44] to facilitate the implementation of fault characteristics.…”

Section: Modal Transformationmentioning

confidence: 99%

Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

2016

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A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this study. Though the three topics are highly correlated, the authors try to discuss them separately, so that one may have a more logical and comprehensive understanding of the concepts without getting confused. Great significance is also attached to the feature extraction process, without which the majority of the methods may not be implemented properly. Fault detection techniques are discussed on the basis of feature extraction. After the overall concepts and general ideas are presented, representative works as well as new progress in the techniques are covered and discussed in detail. One may find the content of this study helpful as a detailed literature review or a practical technical guidance.

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A network distribution power system fault location based on neural eigenvalue algorithm

Cited by 19 publications

References 8 publications

A Review of Fault Diagnosing Methods in Power Transmission Systems

A Review of Fault Diagnosing Methods in Power Transmission Systems

A Comprehensive Review of Fault Location Methods for Distribution Power System

Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

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