High impedance fault detection: A review

Ghaderi, Amin; Ginn, Herbert L.; Mohammadpour, Hossein Ali

doi:10.1016/j.epsr.2016.10.021

Cited by 241 publications

(133 citation statements)

References 99 publications

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“…Readers familiar with the "Partial Discharge" literature, which often quantify such responses with reflectometry, would not be surprised with the results presented herein. Power distribution system HIFs are often discussed as random events with characteristics hard to quantify such as build up, non-linearity, and high intermittency [1], [2]. The specificity and quantitative evidence presented here, therefore, can add to the phenomena understanding, especially regarding the highfrequency domain components.…”

Section: Applicability and Significancementioning

confidence: 82%

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Vegetation High-Impedance Faults’ High-Frequency Signatures via Sparse Coding

Gomes

Ozansoy

Ulhaq

2020

IEEE Trans. Instrum. Meas.

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The behavior of High-Impedance Faults (HIFs) in power distribution systems depends on multiple factors, making it a challenging disturbance to model. If enough data from real staged faults is provided, signal processing techniques can help reveal patterns from a specific type of fault. Such a task is implemented herein by employing the Shift-Invariant Sparse Coding (SISC) technique on a data set of staged vegetation high-impedance faults. The technique facilitates the uncoupling of shifted and convoluted patterns present in the recorded signals from fault tests. The deconvolution of these patterns was then individually studied to identify the possible repeating fault signatures. The work is primarily focused on the investigation of the under-discussed high-frequency faults signals, especially regarding voltage disturbances created by the fault currents. Therefore, the main contribution from this paper is the resulted evidence of consistent behavior from real vegetation HIFs at higher frequencies. These results can enhance phenomena awareness and support future methodologies dealing with these disturbances.

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Section: Applicability and Significancementioning

confidence: 82%

“…The investigation of High-Impedance Faults (HIFs) in power distribution systems comprise an intricate field of research in the contemporary technical literature [1], [2]. Despite considered as a power protection issue, these faults are lowenergy events unlikely to damage power systems' equipment.…”

Section: Introductionmentioning

confidence: 99%

Vegetation High-Impedance Faults’ High-Frequency Signatures via Sparse Coding

Gomes

Ozansoy

Ulhaq

2020

IEEE Trans. Instrum. Meas.

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“…• Asymmetric nature of HIF current: Peak values of current are different in positive and negative half cycle due to the presence of varying break down voltage (Ghaderi et al, 2016;Biswal, 2017).…”

Section: Properties Of High Impedance Faultsmentioning

confidence: 99%

“…• Low and high frequency components: HIF current includes low frequency components due to non-linearity of HIF. Additionally, HIF current also contains high frequency components due to intermittent nature of arc (Ghaderi et al, 2016).…”

Section: Properties Of High Impedance Faultsmentioning

confidence: 99%

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High impedance fault detection and isolation in power distribution networks using support vector machines

Sarwar

Mehmood

Abid

et al. 2020

Journal of King Saud University - Engineering Sciences

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This paper proposes an accurate High Impedance Fault (HIF) detection and isolation scheme in a power distribution network. The proposed schemes utilize the data available from voltage and current sensors. The technique employs multiple algorithms consisting of Principal Component Analysis, Fisher Discriminant Analysis, Binary and Multiclass Support Vector Machine for detection and identification of the high impedance fault. These data driven techniques have been tested on IEEE 13-node distribution network for detection and identification of high impedance faults with broken and unbroken conductor. Further, the robustness of machine learning techniques has also been analysed by examining their performance with variation in loads for different faults. Simulation results for different faults at various locations have shown that proposed methods are fast and accurate in diagnosing high impedance faults. Multiclass Support Vector Machine gives the best result to detect and locate High Impedance Fault accurately. It ensures reliability, security and dependability of the distribution network.

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A novel graph search and machine learning method to detect and locate high impedance fault zone in distribution system

Joga

Sinha

Maharana

2022

Engineering Reports

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High impedance fault (HIF) is difficult to detect by conventional overcurrent protection relays due to the lower fault current values, which are normally lower than the normal current. A fast and reliable algorithm is required to detect this type of fault. This paper proposes a novel method for detecting the location of HIF fault zone in a distribution system by using a novel graph theory‐based zone detection technique along with a Random Search Multilevel Support Vector Machine (RSMSVM) algorithm to classify the faulted zone. Due to shift in‐variance property of “Dual Tree Complex Wavelet Transform (DTCWT),” which has been used, in this paper, to decompose the voltage/current waveform to collect the signature of the signals and feed to the optimized RSMSVM model for classifying fault zone. The proposed method is evaluated on the IEEE 33‐bus system and also IEEE 39 bus test system under normal and noisy conditions. The proposed method is also evaluated for distribution network with the integration of distributed generation.

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High impedance fault detection: A review

Cited by 241 publications

References 99 publications

Vegetation High-Impedance Faults’ High-Frequency Signatures via Sparse Coding

Vegetation High-Impedance Faults’ High-Frequency Signatures via Sparse Coding

High impedance fault detection and isolation in power distribution networks using support vector machines

A novel graph search and machine learning method to detect and locate high impedance fault zone in distribution system

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