Verification of the Wavelet-Based HIF Detecting Algorithm Performance in Solidly Grounded MV Networks

Michalík, Marek; Lukowicz, M.; Rebizant, W.; Lee, Seung-Jae; Kang, Sang-Hee

doi:10.1109/tpwrd.2007.905283

Cited by 40 publications

(18 citation statements)

References 8 publications

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“…The complete algorithm is implemented on a DSP and the results for the measured data from field tests and simulations have shown its reliable performance. The proposed algorithm has shown satisfactory results for all examined cases in which the arc has occurred and the ground fault current was greater than 2A, which in comparison with the published results [12,13] is less restrictive.…”

Section: Introductionsupporting

confidence: 64%

“…Various methods have been presented for HIF detection from 1970s up to now [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17], which are mainly based on revealing some characteristics of the feeder current waveform. Unfortunately, in HIF detection the appropriate characteristics of current waveform are not the ones that can be extracted by the simple readings from the meters on the feeders.…”

Section: Introductionmentioning

confidence: 99%

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Design and implementation of a systematically tunable high impedance fault relay

2010

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Section: Introductionsupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Design and implementation of a systematically tunable high impedance fault relay

2010

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“…The wavelet transform has the capability to extract the signal that has sharp changes, tiny discontinuity and sharp peaks. Also, it is able to identify a small fluctuation occurred in the signal [1,3,6,36].…”

Section: Discrete Wavelet Transform-based Multi-resolution Analysismentioning

confidence: 99%

“…For an underground cable, HIF is normally caused by insulation defects that exposes the conductor to contact with non-conducting elements. Different HIF detection schemes have been proposed in the past [1][2][3][4][5][6][7][8][9][10][11][12]. The process of HIF detection comprises two basic steps; feature extraction and pattern matching or classification.…”

Section: Introductionmentioning

confidence: 99%

“…The process of HIF detection comprises two basic steps; feature extraction and pattern matching or classification. In the feature extraction step, a number of features are extracted from voltage and current signals using various feature extractors or digital signal processing tools including wavelet transform [1][2][3]8,10,13], Fourier transform [14], Prony analysis [15], S-transform [16], TT-transform [17] and phase space reconstruction [18]. Irregularities in the voltage and current waveforms caused by HIF at a certain section produce unique signatures embedded in the extracted features.…”

Section: Introductionmentioning

confidence: 99%

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High impedance fault location in 11kV underground distribution systems using wavelet transforms

Bakar

Ali

Tan

et al. 2014

International Journal of Electrical Power & Energy Systems

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High‐impedance fault location using matching technique and wavelet transform for underground cable distribution network

Ali¹,

Bakar²,

Mokhlis³

et al. 2014

IEEJ Transactions Elec Engng

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Locating the faulty section of a high-impedance fault (HIF) is quite challenging for the underground distribution network of a power system. The complexity of the distribution network, such as branches, nonhomogenous lines, and HIF, contributes to the difficulties in locating the faulty section. In this paper, the shortest distance (SD) technique and a database approach have been proposed to determine the faulty section. A multiresolution analysis based on discrete wavelet transforms is chosen to extract the unique features from voltage signals during the HIF event. The output coefficients from the decomposition process is stored in a database and used as the input data for the SD algorithm. The first, second, and third level of detailed coefficients of the postdisturbance voltage signal were utilized for the identification of the faulty section using the proposed method. A ranking analysis was created to provide a number of possibilities of faulty section. In this paper, a 38-node underground distribution network system in a national grid in Malaysia was modeled using the PSCAD software. The proposed method was able to successfully determine the faulty section.

show abstract

Verification of the Wavelet-Based HIF Detecting Algorithm Performance in Solidly Grounded MV Networks

Cited by 40 publications

References 8 publications

Design and implementation of a systematically tunable high impedance fault relay

Design and implementation of a systematically tunable high impedance fault relay

High impedance fault location in 11kV underground distribution systems using wavelet transforms

High‐impedance fault location using matching technique and wavelet transform for underground cable distribution network

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