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Proceedings ArticleDOI

Wavelet Based Transmission Line Protection Scheme Using Centroid Difference and Support Vector Regression

TLDR
A Wavelet based transmission line protection algorithm which uses centroid difference for fault detection and support vector regression for the fault location and a large number of case studies involving changes in fault impedance, fault incidence angle and fault location have been conducted to establish the performance of the proposed algorithm.
Abstract
This paper presents a Wavelet based transmission line protection algorithm which uses centroid difference for fault detection and support vector regression for the fault location. The sample of three phase currents signals of both the terminals of the line are synchronized and decomposed with Wavelet Transform to obtain the absolute values of approximate coefficients over moving window of a cycle. For the decomposition of current signal dbl mother wavelet is used. Two centroid at each cycle is computed using k-means clustering. The centroid difference is computed at both terminal added to obtain fault index. The fault index is compared with a threshold to detect the faulty phase and to classify the fault. The same approximate coefficients of post fault current transient obtain over half a cycle are used for the estimation of fault location with the help of support vector regression. A large number of case studies involving changes in fault impedance, fault incidence angle and fault location have been conducted to establish the performance of the proposed algorithm.

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References
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Journal ArticleDOI

Combined fuzzy-logic wavelet-based fault classification technique for power system relaying

TL;DR: Results indicate that this approach can be used as an effective tool for high-speed digital relaying, as the correct detection is achieved in less than half a cycle and that computational burden is much simpler than the recently postulated fault classification techniques.
Journal ArticleDOI

A wavelet-fuzzy combined approach for classification and location of transmission line faults

TL;DR: Both classification and location algorithms can be used as effective tools for real-time digital relaying purpose and are immune from effects of faults inception angle, impedance and distance.
Journal ArticleDOI

A wavelet multiresolution analysis for location of faults on transmission lines

TL;DR: Results indicate that the proposed method for the location of faults based on wavelet multiresolution analysis (MRA) is very effective in locating the fault with a high accuracy.
Journal ArticleDOI

Novel filter based ANN approach for short-circuit faults detection, classification and location in power transmission lines

TL;DR: A hybrid framework consisting of a proposed two-stage finite impulse response (FIR) filter, four support vector machines (SVMs), and eleven support vector regressions (SVRs) is implemented in Proteus 6/MATLAB environments and can rapidly detect, classify and locate short-circuit faults in power transmission lines before power outage carried out by protection relays.
Journal ArticleDOI

A wavelet multiresolution analysis approach to fault detection and classification in transmission lines

TL;DR: Simulation results show that this real-time wavelet multiresolution analysis (MRA) based fault detection and classification algorithm is effective and robust, and it is promising in high impedance fault detection.
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