Discrete wavelet transform optimal parameters estimation for arc fault detection in low-voltage residential power networks

2017 ◽  
Vol 143 ◽  
pp. 130-139 ◽  
Author(s):  
Pan Qi ◽  
Slavisa Jovanovic ◽  
Jinmi Lezama ◽  
Patrick Schweitzer
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Discrete Wavelet Transform ◽  
Low Voltage ◽  
Parameters Estimation ◽  
Discrete Wavelet ◽  
Optimal Parameters ◽  
Power Networks

scholarly journals High impedance fault detection in 11 kV overhead line with discrete wavelet transform and independent component analysis

2021 ◽  
Vol 24 (2) ◽  
pp. 661
Author(s):  
Md Ferdouse Hossain Bhuiya ◽  
Rohaiza Hamdan ◽  
Dur Mohammad Soomro ◽  
Abdelrehman Omer Idris ◽  
Hussain Sharif
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Independent Component Analysis ◽  
Discrete Wavelet Transform ◽  
Component Analysis ◽  
Independent Component ◽  
Discrete Wavelet ◽  
Advanced Technique ◽  
High Impedance ◽  
High Impedance Fault

This paper proposes an analysis of high-impedance fault detection algorithms for medium voltage distribution lines based on the discrete wavelet transform (DWT) technique and a more advanced technique named independent component analysis (ICA) independently. Three-phase distribution line model and two diodes high impedance fault model, which represents the unsymmetrical fault current of electric arc, simulated using MATLAB/Simulink. High impedance fault (HIF) detection algorithm initially analyzes the sampled current waveforms through DWT and the resultant third level high-frequency components “d3” coefficients are analyzed through one cycle moving window approach. The proposed algorithm successfully detects any HIF in the distribution current even if there is a slight or no difference in the amplitude of the HIF and the waveform of the phase current. On the other hand, the ICA more developed algorithm than DWT successfully separated the noise signals from the obtained current waveforms and HIF noise signals can be differentiated with non-HIF noise signals. Because of this reason ICA is chosen in this research. The detected HIF current can be from 50 ma and up.

scholarly journals WAVELET-BASED TRANSMISSION LINE FAULT DETECTION AND CLASSIFICATION

2013 ◽  
pp. 58-63
Author(s):  
KULKARNISAKEKAR SUMANT SUDHIR ◽  
R.P. HASABE
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Power System ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Fault Detection And Classification ◽  
Power System Faults ◽  
Detail Coefficient

An appropriate method of fault detection and classification of power system transmission line using discrete wavelet transform is proposed in this paper. The detection is carried out by the analysis of the detail coefficients energy of phase currents. Discrete Wavelet Transform (DWT) analysis of the transient disturbance caused as a result of occurrence faults is performed. The work represented in this paper is focused on classification of simple power system faults using the maximum detail coefficient, energy of the signal and the ratio of energy change of each type of simple simulated fault are characteristic in nature and used for distinguishing fault types.

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