A novel selectivity technique for high impedance arcing fault detection in compensated MV networks

Abstract

SUMMARYIn this paper, the initial transients due to arc reignitions associated with high impedance faults caused by leaning trees are extracted using discrete wavelet transform (DWT). In this way, the fault occurrence is localized. The feature extraction is carried out for the phase quantities corresponding to a band frequency 12.5-6.25 kHz. The detection security is enhanced because the DWT corresponds to the periodicity of these transients. The selectivity term of the faulty feeder is based on a novel technique, in which the power polarity is examined. This power is mathematically processed by multiplying the DWT detail coefficients of the phase voltage and current for each feeder. Its polarity identifies the faulty feeder. In order to reduce the computational burden of the technique, the extraction of the fault features from the residual components is examined. The same methodology of computing the power is considered by taking into account the residual voltage and current detail coefficients where the proposed algorithm performs best. Test cases provide evidence of the efficacy of the proposed technique.

Voltage Based Detection Method for High Impedance Fault in a Distribution System

“…where g is the time-varying arc conductance, G is the stationary arc conductance, |i| is the absolute value of the arc current, U arc is a constant arc voltage parameter, s is the arc time constant, and A and B are constants control signals are generated to distinguish between arcing and dielectric periods to fulfill the re-ignition instant after each zero crossing [21]. …”

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

“…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.…”

“…Unlike LIF, comparatively less research studies have been conducted to identify the HIF location. There are several approaches to determine the HIF location such as network topology technique [5][6][7][36][37][38][39], travelling wave technique [40][41][42][43] and knowledgebased technique [44][45][46][47][48].…”

Operation evaluation of DWT-based earth fault detection in unearthed MV networks

“…In [1], [5], a detection technique was introduced to detect a severe earth fault due to leaning trees. This fault is extremely difficult to be detected due to the tree resistance which is several hundreds kilo ohms [6], [7].…”

“…The faults due to leaning tree are modeled and experimentally verified as addressed in [6]. The detection of this fault type has been discussed and the faulty section has been estimated using a novel selectivity technique as reported in [1], [5]. The detection was based on an absolute sum of DWT detail coefficients of the residual voltages.…”