An Improved Method for Digital Relaying of Transmission Lines

Mahanty, R. N.; Gupta, Preeti

doi:10.1080/15325000490257782

Cited by 19 publications

(10 citation statements)

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“…The positive and negative sequence of source impedance (Z s ) are (0.45 + j 5) per phase, and the zero sequence impedance is one and half times the positive sequence impedance. An active power of 500 MW and reactive power (inductive) of 20 MVAR have been considered as load for the case studies [12].…”

Section: Simulation and Results For Comparative Studymentioning

confidence: 99%

“…Wavelet applications for transmission line faults analysis are enriched by some interesting research studies [3][4][5][6][7][8][9][10][11][12][13][14][15][16]. Therefore, an attempt is made for a brief exposition of wavelet transform to give an adequate emphasis to depict the real-time implementation of fault classification algorithm.…”

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

“…The actual implementation of DWT is done by multi-resolution analysis (MRA) [12]. By MRA a signal can be analyzed at different frequency bands with different resolutions.…”

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

“…The advantage of wavelet analysis over short time Fourier analysis is that whereas the latter uses a single analysis window, the former used short windows at high frequencies and long windows at low frequencies. The continuous 1-dimension wavelet transform (CWT) of a signal x(t) is defined as [12] CWT…”

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

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A DSP based frequency domain approach for classification of transmission line faults

Reddy

Mohanta

2008

Digital Signal Processing

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Section: Simulation and Results For Comparative Studymentioning

confidence: 99%

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

“…The actual implementation of DWT is done by multi-resolution analysis (MRA) [12]. By MRA a signal can be analyzed at different frequency bands with different resolutions.…”

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

Section: Fault Classification Using Wavelet Mramentioning

confidence: 99%

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A DSP based frequency domain approach for classification of transmission line faults

Reddy

Mohanta

2008

Digital Signal Processing

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“…Involving only the level-1 details ensures less computational burden and a fast speed. The proposed scheme is a modified version of a previous scheme proposed by the authors [5]. The previous algorithm was modified for better identification of faulty phases, particularly in those of L-L-G and L-L-L faults.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Fault Classification Methods Based on Wavelet Analysis and ANN

Mahanty

Gupta²

2006

Electric Power Components and Systems

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Two methods for classification of transmission line faults are presented and compared, one based on a wavelet analysis and the other on an artificial neural network (ANN). While the wavelet analysis based approach requires consideration of wavelet multiresolution analysis (MRA) level-1 details of the three phase currents and delta currents, the ANN based approach requires the samples of three phase currents as inputs. Simulation studies using EMTP and MATLAB and considering wide variations in fault location, fault inception angle, and fault point resistance for different types of faults have shown that the wavelet analysis based method has an edge over the ANN based method.

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Single-Phase Fault Location in Four-Circuit Transmission Lines Based on Wavelet Analysis Using ANFIS

khaleghi

Sadegh

2019

J. Electr. Eng. Technol.

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This paper presents an efficient and effective method to determine the location of the single phase to ground fault in fourcircuit transmission lines. In the proposed method, wavelet analysis based on advanced signal processing techniques are used to extract important features and record the dynamic characteristics of the fault signal using current sampled data of one side of the line. In this regard, the ANFIS network is used to find the relationship between the obtained characteristics from wavelet signal analysis of the fault signal and the changes in different fault conditions. In proposed method, there is no need to know the type of the fault or line information. Also, determination of faulty circuit and the use of intelligent methods to reduce computations are among the advantages of the proposed method. Studies and simulations have been implemented on a four-circuit transmission line of 500 kV and 200 km in PSCAD software. The results of wavelet analysis have been applied as an input of ANFIS network in MATLAB software. The results of the simulations are based on the implementation of different fault conditions, including the faulty circuit, fault location, fault inception, and fault resistance. These results indicate the high accuracy of the proposed method.

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An Improved Method for Digital Relaying of Transmission Lines

Cited by 19 publications

References 0 publications

A DSP based frequency domain approach for classification of transmission line faults

A DSP based frequency domain approach for classification of transmission line faults

Comparison of Fault Classification Methods Based on Wavelet Analysis and ANN

Single-Phase Fault Location in Four-Circuit Transmission Lines Based on Wavelet Analysis Using ANFIS

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