A Review of Fault Location Algorithms Utilising Travelling Wave, Wavelet Transform and Multi-Resolution Analysis Techniques

Buthelezi, K. S.; Musasa, Kabeya; Leoaneka, Moketjema Clarence

doi:10.1109/saupec55179.2022.9730632

Cited by 4 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar to the wavelet transform method [18][19][20], the method proposed in this paper also belongs to the traveling wave method in essence. The difference lies in the identification algorithm of the arrival time of the fault traveling wave: the wavelet transform method uses the wavelet transform to extract the high-frequency transient; The method in this paper is not to directly extract the highfrequency transient, but to extract the identifier quantity corresponding to the high-frequency transient.…”

Section: Introductionmentioning

confidence: 99%

Identification Method for Pulse Wave Resulted From Fault Transient of Overhead Transmission Line

Liu

Zhou

et al. 2023

IEEE Access

View full text Add to dashboard Cite

This paper presents a simple and effective method to extract the identification quantity of transient pulse waveform produced by the overhead transmission line short-circuit fault. This method employs the second-order time harmonic equation of the power frequency component to convert the fault full-wave data. After the conversion, only the identification quantity remains. This method can amplify high-frequency spectral content by the times of the square of the angular frequency, and hence improve the sensitivity of identifying fault transient. Using the identification quantity, one can clearly observe the arrival time and relative intensity of fault transient. A three-phase half wavelength transmission line of 50Hz/3000km is simulated with PSCAD to illuminate the effectiveness of this method. The effects of fault type, soil resistivity, fault resistance, power frequency fluctuation, sampling rate, transposition length,fault inception angle and white noise are analyzed. Calculated results show that this method can distinguish different fault type and can work effectively at low sampling rate down to 10kHz. This method is helpful for improving the performance of the traveling-wave based fault location method.

show abstract

Section: Introductionmentioning

confidence: 99%