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Proceedings ArticleDOI

Transmission line faults detection, classification, and location using Discrete Wavelet Transform

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TLDR
The proposed system uses Discrete Wavelet Transform (DWT) which is widely used in recent times for power system protection and promises the result by detecting, classifying and locating all the ten faults possible in the transmission line of the power system.
Abstract
Transmission line is a vital component that acts as a bridge between the generating stations and end users In the power system, reliability and stability must be ensured to provide continuity of service Transmission lines run over several kilometers will have the chance for occurrence of fault In order to maintain stability, faults should be cleared at short span of time with recent advancements in signal processing In this paper, a novel technique for the protection of transmission lines is proposed The proposed system uses Discrete Wavelet Transform (DWT) which is widely used in recent times for power system protection DWT is used here to extract the hidden factors from the fault signals by performing decomposition at different levels Daubechies wavelet “dB6” is used with single level decomposition and adaptive threshold is calculated to discriminate and detect the faulty phase The location of faults is carried out by obtaining the local fault information and remote location fault information along with the transmission line length The system is independent of any statistical system data and has negligible fault resistance Test system is modeled and fault signals are generated to test the reliability of the algorithm The proposed system promises the result by detecting, classifying and locating all the ten faults possible in the transmission line of the power system

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Citations
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Journal ArticleDOI

Critical aspects on wavelet transforms based fault identification procedures in HV transmission line

TL;DR: In this article, the authors proposed a sensitive and automated fault identification scheme to solve the existing challenges such as high-impedance faults (HIFs), nonlinear modelling of arcing etc.
Journal ArticleDOI

Algorithm for Fault Location and Classification on Parallel Transmission Line Using Wavelet Based on Clarke’s Transformation

TL;DR: The simulation results using PSCAD / EMTDC software showed that the proposed algorithm could distinguish internal and external faults to get the current signal in the transformation of a signal fault.
Journal ArticleDOI

An investigated reactive power measurements-based fault-identification scheme for teed transmission lines

TL;DR: A novel scheme for fault detection, classification and faulted-phase/s identification on the basis of reactive-power components of TTLs, designed to be insensitive to different fault resistances, different fault locations, and inception angles is proposed.
Proceedings ArticleDOI

Faults detection and diagnosis of transmission lines using wavelet transformed based technique

TL;DR: This paper presents modern solution of fault detection and diagnosis of overhead transmission lines by implementing Discrete Wavelet Transform (DWT) and has been successfully tested for various categories of faults at different operating conditions.
Proceedings ArticleDOI

Selection of proper input pattern in fuzzy logic algorithm for classifying the fault type in underground distribution system

TL;DR: The obtained results in term of average accuracy have shown that the maximum ratio of DWT can achieved satisfactory accuracy in fault type classification.
References
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A theory for multiresolution signal decomposition: the wavelet representation

TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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Power quality detection and classification using wavelet-multiresolution signal decomposition

TL;DR: In this paper, a multiresolution signal decomposition technique is used to detect and localize transient events and furthermore classify different power quality disturbances, which can also be used to distinguish among similar disturbances.
Journal ArticleDOI

Fault detection and classification in transmission lines based on wavelet transform and ANN

TL;DR: In this article, the fault detection and its clearing time are determined based on a set of rules obtained from the current waveform analysis in time and wavelet domains, which is able to single out faults from other power quality disturbances, such as voltage sags and oscillatory transients, which are common in power systems operation.
Journal ArticleDOI

Wavelets: a new tool for the resonant grounded power distribution systems relaying

TL;DR: The wavelet transform of a signal consists in measuring the "similarity" between the signal and a set of translated and scaled versions of a "mother wavelet" as discussed by the authors.
Journal ArticleDOI

Wavelets for the analysis and compression of power system disturbances

TL;DR: In this paper, the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms were evaluated using an actual power system disturbance from a digital fault recorder and the application of wavelet compression in power monitoring to mitigate against data communications overheads.
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