High-Impedance Fault Detection Using Discrete Wavelet Transform and Frequency Range and RMS Conversion

Lai, T.M.; Snider, L.A.; Lo, Edward Chin Man; Sutanto, Danny

doi:10.1109/tpwrd.2004.837836

Cited by 199 publications

(97 citation statements)

References 17 publications

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“…Coupling capacitor voltage transformers (CCVT) is a measuring transforming that is widely used in transmission line for voltage measurement and can be used for the extraction of transient signals. In reference [29], it is pointed out that CCVT may have several resonant models and the frequency response may present obvious According to [32][33][34], the performance of wavelet transform is great in capturing the transient wave-head. Thus, the Daubechies 6 (db6) wavelet is used to compose the transient wave-head into four levels.…”

Section: Fault Location Based On the Time Difference Of Modesmentioning

confidence: 99%

Asynchronous Fault Location in Transmission Lines Considering Accurate Variation of the Ground-Mode Traveling Wave Velocity

et al. 2017

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This paper proposes a grounding fault location method in transmission lines based on time difference of arrival (TDOA) of ground-mode and aerial-mode traveling waves (TWs). The frequency-dependent characteristics of transmission lines cause different frequencies to have different attenuations and phase lags of different frequency components in traveling waves, which leads to the change of TWs velocities with different propagation distances. Due to these different propagation paths, the wave velocity variations of ground-mode should be considered as a main variable while the velocity of aerial-mode can be seen as a constant factor. A quadratic function that can illustrate the tendency of variation of ground-mode wave velocity is proposed by considering the relation between the wave velocity and fault distance. The least squares method is used to solve the quadratic function of different lines. Combining the quadratic formula and the incident TWs of each mode detected at both terminals of the line, a novel fault location method is proposed. First, according to the maximum and minimum ground-mode velocities, a fault scope can be acquired. Then, more accurate fault scopes and ground-mode velocities can be obtained by iteration computation. Finally, an accurate fault position is acquired when the fault scope is sufficiently small. PSCAD/EMTDC software is used to conduct fault simulations in order to verify the feasibility and accuracy of the method.

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Section: Fault Location Based On the Time Difference Of Modesmentioning

confidence: 99%

Asynchronous Fault Location in Transmission Lines Considering Accurate Variation of the Ground-Mode Traveling Wave Velocity

et al. 2017

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“…Identification techniques generally contain two vital steps: feature extraction and classification [2]. For many years, some protection engineers and researchers had introduced numerous feature extraction and classification techniques such as digital signal processing [3], fractal analysis [4], wavelet transform (WT) [5][6][7][8][9][10], crest factor [11], coefficient of variation [11], mathematical morphology [12], Kalman filtering [13], decision tree [14] etc. and various classifiers have been used such as Bays, nearest neighbor rule (NNR), artificial neural network (ANN) [15], ANFIS (adaptive neuro-fuzzy inference system) [16] etc.…”

Section: Introductionmentioning

confidence: 99%

A Universal High Impedance Fault Detection Technique for Distribution System Using S-Transform and Pattern Recognition

Mishra

Routray

Rout

2016

Technol Econ Smart Grids Sustain Energy

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This paper describes a new method for high impedance fault (HIF) detection based on s-transform (ST) and pattern recognition technique. Conventional distance, over current and ground fault relays are difficult to apply for High Impedance Fault (HIF) detection in distribution line because of sensitivity, diversity, selectivity issues in case of low value of fault current. Recently, s-transform has been successfully applied for different power system protection problem. It is a very useful tool to analyze transient fault signal to provide both time and frequency information unlike Fourier transform and the same has been considered for high impedance fault detection in this work. The features extracted using s-transform to train and test the two different intelligent classifier like artificial neural network (ANN) and support vector machine (SVM) separately, to discriminate the HIF with other transient phenomenon (Load switching, capacitor Switching) and also normal fault condition. A comparative study of these two classifiers has been reported based on their detection accuracy. It has been found that the proposed techniques are highly effective for high impedance fault detection under a wide range of operating conditions and noisy environment in a high voltage distribution

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“…Many fault features have been extracted and the highly recognized ones are: radiation behavior [1][2][3] and harmonic distortions in voltage and current [4][5][6][7][8][9]. Plenty of detection algorithms have been proposed and analyzed, including electromagnetic radiation based algorithms [3], harmonic based algorithms [4][5][6][7][8][9][10][11][12][13][14], wavelet based algorithms [15][16][17], instantaneous power based algorithms [18], and some intelligent detection algorithms [19,20]. Due to the obvious 3 rd harmonic characteristic of HIFs, the harmonic based algorithms are the most commonly adopted in industrial application.…”

Section: Introductionmentioning

confidence: 99%

Arc flash fault detection in wind farm collection feeders based on current waveform analysis

Wang

Geng

et al. 2016

J. Mod. Power Syst. Clean Energy

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High impedance faults (HIFs) are easy to occur in collective feeders in wind farms and may cause the cascading of wind generators tripping. This kind of faults is difficult to be detected by traditional relay or fuse due to the limited fault current values and the situation is worse in wind farms. The mostly adopted HIF detection algorithms are based on the 3 rd harmonic characteristic of the fault zero-sequence currents, whereas these 3 rd harmonics are very easy to be polluted by wind power back-to-back converters. In response to this problem, the typical harmonic characteristic of HIF arc flash based on Mayr's arc model is first analyzed, and the typical fault waveforms of HIF in wind farm are presented. Then the performance of the harmonic based HIF detection algorithm is discussed, and a novel detection algorithm is proposed from the viewpoint of time domain, focusing on the convex and concave characteristic of zero-sequence current at zerocrossing points. A HIFs detection (HIFD) prototype implementing the proposed algorithm has been developed. The sensitivity and security of the algorithm are proved by field data and RTDS experiments.

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High-Impedance Fault Detection Using Discrete Wavelet Transform and Frequency Range and RMS Conversion

Cited by 199 publications

References 17 publications

Asynchronous Fault Location in Transmission Lines Considering Accurate Variation of the Ground-Mode Traveling Wave Velocity

Asynchronous Fault Location in Transmission Lines Considering Accurate Variation of the Ground-Mode Traveling Wave Velocity

A Universal High Impedance Fault Detection Technique for Distribution System Using S-Transform and Pattern Recognition

Arc flash fault detection in wind farm collection feeders based on current waveform analysis

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