High-Impedance Fault Detection Based on Nonlinear Voltage–Current Characteristic Profile Identification

High Impedance Fault Detection using Advanced Distortion Detection Technique

“…The third category consists of techniques based on combining algorithms/tools to obtain the desired effect. Traditional time-domain based techniques used for HIF detection include the use of processing tools based on mathematical morphology to detect HIF [2], comparison of negative and positive current peaks to calculate current flicker and determine asymmetry in fault current [3], extracting signatures from current waveforms by observing change in ratio between substation and line ground resistances during HIF [4], ratio ground relaying based techniques [5], analyzing chaotic properties of HIF by fractal geometry techniques [6], transient analysis of disturbances to observe change in crest factor [7], profile identification of nonlinear voltage-current characteristics of HIF [8] and superimposition of voltage signals of certain frequencies to find HIF signatures [9]. Some of the traditional frequency-domain based techniques include monitoring of feeder current to find burst noise signal indicating HIF event [10], a range of algorithms based on lower order harmonics in [11]- [15].…”

A novel discrete wavelet transform‐based graphical language classifier for identification of high‐impedance fault in distribution power system

“…Thus, it requires an effective fault management scheme for rapid detection and isolation of fault, to restrict the escalation of faults into healthy part of the power network. With the increasing complexity of distribution network, the identification and location of fault is a cumbersome process by reliance on human operators . Thus, the proposed research work paves the way for automatic monitoring of system state by identifying and displaying the type of fault occur in the distributed control center.…”

High Impedance Fault Detection in MV Distribution Network using Discrete Wavelet Transform and Adaptive Neuro-Fuzzy Inference System

“…The various abnormalities that occur in electrical distribution networks are capacitor switching, high impedance faults, line faults and sudden load rejection and so on. Among these disturbances, the detection of high impedance faults on electrical power system networks have been one of the most challenging phenomenon faced by the today's electric utility industry [1]. Over-theyears, the typical protection schemes used to detect the fault in the system involves only the low impedance faults (i.e.…”

“…The results indicate that the proposed method is more efficient to identify and discriminate the high impedance fault accurately from other power system faults in the system. [1,2]. To mitigate such crisis, some of the conventional schemes such as minimum reactance approach, voltage and current pattern of the systems and the transients associated with these waves were used to locate the faults in the system [3][4][5][6].Researchers have resented a large number of high impedance fault identification algorithms using a combination of computational intelligence methods such as ANN, Fuzzy, harmonic component analysis using Extreme Learning Machine (ELM), decision tree approach, Bayes classification, nearest neighbor rule approach etc.…”

“…The results indicate that the proposed method is more efficient to identify and discriminate the high impedance fault accurately from other power system faults in the system. [1,2]. To mitigate such crisis, some of the conventional schemes such as minimum reactance approach, voltage and current pattern of the systems and the transients associated with these waves were used to locate the faults in the system [3][4][5][6].…”