The application of neural networks and Clarke-Concordia transformation in fault location on distribution power systems

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

doi:10.1109/tdc.2002.1177783

Cited by 21 publications

(9 citation statements)

References 7 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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“…In reference [70], the application of neural networks and Clarke's transformation in fault location on distribution power systems is presented. The locator is able to identify and locate all types of faults with good results.…”

Section: Chapter 2 -Fault In Transmission Cables and Current Fault Lomentioning

confidence: 99%

Online Location of Faults on AC Cables in Underground Transmission Systems

Jensen

2014

Springer Theses

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University in partial fulfilment of the requirements for the PhD degree in Electrical Engineering. The research has been carried out between the 1.09.2010 and the 15.07.2013 at the Department of Energy Technology for Energinet.dk by which I was hired as a PhD-student for the entire project period.The project has been followed full time by two supervisors: Professor Claus Leth Bak (Department of Energy Technology) and Dr. Unnur Stella Gudmundsdottir (Energinet.dk).Energinet.dk has fully funded the research leading to this thesis "Online Location of Faults on AC Cables in Underground Transmission Systems". This funding has been vital for this research project. Travelling to conferences, two visits at forging research institutions, renting of laboratory equipment and performance of and field measurements was made possible thanks to support from the company. During the projet period I supervised two master projects and thought one semester course in power system transients.The scientific papers written as a part of this PhD are included in the back of both the printed version of the thesis as well as in the PDF-file. The papers should not be considered a part of this monograph, but are enclosed if the reader is interested.This thesis has five parts and appendices. An overall literature reference list is presented at the end of the main report. A list of the authored publications is presented at the end of the thesis. Literature references are shown as [i], where i is the number of the literature in the reference list. Tables, figures and equations are shown as C.F, where C is the chapter number and F is a unique number for the figure or table. AcknowledgementsI owe gratitude to many people who helped me in different ways. I would like to thank:• My supervisors, Claus Leth Bak and Unnur Stella Gudmundsdottir for all their help, comments, and many technical discussions during the last three years.• Carl-Erik Madsen, Henrik Kastberg and Carl Willi Hansen for their help with carrying out the field measurements. In the same regards, a very special thanks is extended to Filipe Faria da Silva and Unnur Stella Gudmundsdottir for participating during all measurements.• Filipe Faria da Silva for numerous technical discussions, for reading large parts of the thesis and for many good times in the office.• Rasmus Schmidt Olsen, Unnur Stella Gudmundsdottir, Joachim Holbøll, Per Balle Holst, Poul Erik Pedersen, Thomas Kvarts, Carsten Rasmussen, Claus Leth Bak and Bjarne Søndergaard Bukh for their contributions and comments during the project period.• Everyone at the transmission department at Energinet.dk for their contributions.• Professor Ali Abur for his hospitality and comments to my work during my three month stay at North Eastern University in Boston 2012.• • A special thanks to Dr. Jeewantha Da Silva for numerous discussions, valuable advice and guidance throughout the entire project period.• To Prof. Athula Rajapakse and PhD-student Kasun Nanayakkara both from University of Manitoba, Winnipeg, Manitoba for valuable discuss...

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“…Unfortunately, the determination of the propagation velocity is based on the real‐time calculation of fault port equivalent parameter, which is impractical in terms of industrial application due to the low error tolerance on signal sampling; such problems also exist in Refs . In addition, several authors have indicated that the fault tolerance of Prony's method , artificial neural network‐based method , and genetic algorithm‐based method may have great performance upon fault tolerance and resistive tolerance. However, previous studies have revealed that the universal defect of these methodologies is that they need to be trained offline with a large number of training samples and their accuracy is not immune to the change of the operation conditions of the distribution network.…”

Section: Introductionmentioning

confidence: 99%

An Online Faulty Sub‐Feeder Identification Method for the NUGS Single‐Phase Earth Fault Based on the Faulty Phase Current Feature Recognition

Lin

Liu

Lyu

et al. 2018

IEEJ Transactions Elec Engng

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Single-phase earthing is a type of fault that occurs frequently in a distribution network. To improve the reliability of the power supply, neutral un-effectively grounded system (NUGS) is adopted in many countries. However, it will lead to the difficulty of identification of the faulted components. Existing faulty sub-feeder identification methods place severe limit on field feasibility in various aspects when dealing with this problem. In this paper, an online single-phase earth faulty sub-feeder identification method based on the faulty phase current feature recognition is introduced and assessed according to the universal distribution characteristics of the high-frequency transient components. In comparison with existing location methods, the proposed method is independent of zero-sequence current measurement and has the natural faulty feeder selection capability. Besides, it can be implemented economically by virtue of the existing distribution automation system in the NUGS. The effectiveness of the proposed method under various fault conditions is verified by Power Systems Computer Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC) simulation and comparison studies.

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The application of neural networks and Clarke-Concordia transformation in fault location on distribution power systems

Cited by 21 publications

References 7 publications

A Review of Fault Diagnosing Methods in Power Transmission Systems

A Review of Fault Diagnosing Methods in Power Transmission Systems

Online Location of Faults on AC Cables in Underground Transmission Systems

An Online Faulty Sub‐Feeder Identification Method for the NUGS Single‐Phase Earth Fault Based on the Faulty Phase Current Feature Recognition

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