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

Chen, Kunjin; Huang, Caowei; He, Jinliang

doi:10.1049/hve.2016.0005

Cited by 292 publications

(141 citation statements)

References 136 publications

(180 reference statements)

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“…The idea is based on the classic concept of optimal separation hyperplane, where the separation vector is expressed as a function of training samples. Likewise, the theory of statistical learning incorporates a series of aspects that give the SVM the generalization capacity superior to that of other learning methods [20]. The ability to generalize is mainly a consequence of margin maximization.…”

Section: Basics Of Svmmentioning

confidence: 99%

A Novel Approach for the Detection, Classification and Localization of Transmission Lines Faults using Wavelet Transform and Support Vector Machines Classifier

S.Wani¹,

Singh²

2018

IJET

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Over the time, techniques have been developed whose approach has been linked mainly to the diagnosis of faults, which is why over the years these techniques have been improved little by little in order to complement or at best cases innovate the traditional methods used for the detection of faults from the mathematical point of view relying mainly on sophisticated methods and some of them related to artificial intelligence. Taking into account the aforementioned, in this paper we propose the use one of the branches of artificial intelligence, specifically automatic learning through the tool known as Support Vector Machines (SVM) to find a method with which is feasible to identify and classify the type of fault. For the creation of the mathematical model it is essential to have a database. The database consists of input data and output data, the input data are the detail coefficients obtained from the decomposition of the current and voltage signals using the Discrete Wavelet Transform (DWT). Meanwhile, the output data are the labels assigned and with which the model can identify and classify the different types of faults. Both current signals and voltage signals are generated based on an extensive simulation of faults along the longest transmission line that has a test system.

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Section: Basics Of Svmmentioning

confidence: 99%

A Novel Approach for the Detection, Classification and Localization of Transmission Lines Faults using Wavelet Transform and Support Vector Machines Classifier

S.Wani¹,

Singh²

2018

IJET

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“…But the reviewed works do not include fault location methods for DG‐integrated system. Authors in a previous study presented a review on the techniques used for fault detection, classification, and location in distribution systems as well as transmission systems; importance is also given to the feature extraction methods on which the methods are implemented. Telukunta et al, surveyed fault location challenges associated with the distribution system under bulk penetration of RE sources.…”

Section: Introductionmentioning

confidence: 99%

A Literature Review on Methodologies of Fault Location in the Distribution System with Distributed Generation

Kumar

Saxena

2020

Energy Tech

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In the last decade, with increasing power supply from distributed generation (DG) to the distribution system, the traditional passive radial distribution systems transformed into an active multisource system. The nature of fault location schemes designed for the distribution system has traditionally been based on unidirectional power flow assumptions, making them ineffective for a distribution system with a higher level of DG penetration. New grid regulations require DGs to remain connected to the system in the event of a fault to provide support to the grid and improve system reliability. This makes the fault location process important as the timely location of a fault speeds up the restoration process, which improves the system reliability. Herein, providing a comprehensive review of the available techniques for fault location in the distribution system with DG penetration is focused on. An analysis is given on the shortcomings of traditional protection methods when applied to DG‐integrated distribution systems. A comparative analysis is carried out in which the merit and demerit of each technique is assessed. A discussion on some other important technical issues arising due to DG integration, such as effects on the stability of the distribution system, is also given.

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“…Detection and classification of faults on HV power lines is crucial for stable and reliable power system operation. Various methods for detection, classification and location of faults on HV power lines have been studied, taking advantage of digital signal processing algorithms and machine learning methods [8]. The common characteristic of all available approaches is to utilize measured phase voltage and current signals or fault-generated transient phenomena [9,10].…”

Section: Introductionmentioning

confidence: 99%

Communication Characteristics of Faulted Overhead High Voltage Power Lines at Low Radio Frequencies

2017

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This paper derives a model of high-voltage overhead power line under fault conditions at low radio frequencies. The derived model is essential for design of communication systems to reliably transfer information over high voltage power lines. In addition, the model can also benefit advanced systems for power-line fault detection and classification exploiting the phenomenon of changed conditions on faulted power line, resulting in change of low radio frequency signal propagation. The methodology used in the paper is based on the multiconductor system analysis and propagation of electromagnetic waves over the power lines. The model for the high voltage power line under normal operation is validated using actual measurements obtained on 400 kV power line.

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

Cited by 292 publications

References 136 publications

A Novel Approach for the Detection, Classification and Localization of Transmission Lines Faults using Wavelet Transform and Support Vector Machines Classifier

A Novel Approach for the Detection, Classification and Localization of Transmission Lines Faults using Wavelet Transform and Support Vector Machines Classifier

A Literature Review on Methodologies of Fault Location in the Distribution System with Distributed Generation

Communication Characteristics of Faulted Overhead High Voltage Power Lines at Low Radio Frequencies

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