Detecting arcing downed-wires using fault current flicker and half-cycle asymmetry

Abstract

The downed-wires problem, known as high impedance faults, is described. A high voltage laboratory setup was devised to investigate the phenomenon. The laboratory model results agreed with field test results, and previous research efforts. The arcing fault model was justified. The setup was used ~ as a source of fault current signal.A simple approach was taken to design an arcing fault detector. The algorithm utilizes the random behauior of the fault current. It compares the positive and negative current peaks in one cycle to those in the next cycle to measure the flicker in the current signal. The asymmetry of the current is calculated by comparing the positive peak to the negative peak, for each cycle: the moving window length is half a cycle. Both values are used as a signature of arcing. The result is filtered and compared with a suitable detection threshold.The algorithm was tested by traces of normal load, and no-load current disturbed by currents of faults on dry and wet soil, arc welders, computers, and fluorescent light loads, as well as short circuit currents. The algorithm performed well under the test conditions, except for the arc welder load. This load is also a source of insecurity for other algorithms. The detection criterion will be integrated with another detection method to improve the security during arcing load events.On-line testing is required to demonstrate algorithm dependability.

Evaluation of a new proposal for an arcing fault detection method based on wavelet packet analysis

“…An identification condition was set up to recognize AF if at least one of the Counter (4,1) Counter (4,2) or Counter (4,3) reaches its respective maximum and simultaneously at least one of Counter (4,5) or Counter (4,6) also reaches its maximum. When more than one of the Counter (4,1) , Counter (4,2) and Counter (4,3) exceed their respective maxima, the HIF condition is also satisfied.…”

“…In the time domain, arc detection algorithms have been proposed based on arc current waveform [1] and on the random behaviour of the arc appearance [2]. In the frequency domain, using the Fourier Transform, several articles have been published based on harmonic components [3][4][5][6], interharmonic components [7] and high-frequency spectra [8].…”

Fault Locating, Prediction and Protection (FLPPS)

“…Current flicker: In [92], an algorithm is proposed based on the random behavior of arcing faults as determined by the flicker and asymmetry of the arcing fault current. The current flicker is calculated by comparing the positive and negative peaks in one cycle to the previous values.…”

“…In [92], tests were performed in high voltage laboratory at the University of Manitoba to collect HIF data under controlled conditions in 1994. For these tests, a 25 kVA, 240/7200 Volt, 105/3.5 Amp, and 1.5 % impedance, distribution transformer energized from 100 A, 208 V, and 60 Hz was used.…”

The Use of Artificial Neural Networks in the Theoretical Investigation of Faults in Transmission Lines

“…Both factors increase the risk of major power outages. After a blackout, power needs to be restored as quickly and reliably as possible and, consequently, detailed restoration plans are necessary [1][2][3][4][5]. Previous research for detecting faults on transmission lines includes methods based on monitoring power frequency quantities such as load and ground current levels and sequence voltages and currents on the source side of the fault location.…”