High-impedance faults in power distribution systems: A narrative of the field’s developments

Gomes, Douglas Pinto Sampaio; Ozansoy, Cagil

doi:10.1016/j.isatra.2021.02.018

Cited by 19 publications

(13 citation statements)

References 77 publications

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“…They occur due to the contact between energized conductors and high impedance surfaces, such as vegetation, asphalt, sand, grass, or cement. They can occur when conductors break [2] or when the conductor contacts vegetation [3]. One of the main problems related to HIFs is the risk of exposing humans and animals to electric shock and causing bushfires [3].…”

Section: Introductionmentioning

confidence: 99%

“…They can occur when conductors break [2] or when the conductor contacts vegetation [3]. One of the main problems related to HIFs is the risk of exposing humans and animals to electric shock and causing bushfires [3]. HIFs can also cause interruption of the electricity supply when it results in a conductor rupture.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the previously mentioned issues, it is essential to develop solutions for HIF protection on DSs. The interest in developing studies regarding this type of fault started in the 70s [3]. Since then, efforts have been mainly focused on fault detection.…”

Section: Introductionmentioning

confidence: 99%

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High Impedance Fault Location Methods: Review and Harmonic Selection-Based Analysis

Lopes

Menezes

Gomes

et al. 2023

IEEE Open J. Power Energy

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High Impedance Faults (HIFs) are recurring events in electrical Distribution Systems (DSs) and occur by the contact between energized conductors and high impedance surfaces. HIFs may pose hazards to living beings and cause bushfires. However, the HIF protection has not been completely solved due to the small fault current and varying impedance, inhibiting traditional protection techniques from functioning correctly. In the literature, researchers have mainly focused on detection techniques. Thus, the development of HIF Location Methods (HIFLMs) is recent, and evidences for conclusive solutions are still lacking. Moreover, to this date, no existing study reviews the main challenges concerning HIFLMs in DSs. This paper proposes a systematic analysis of the common stages to design the main existing HIFLMs. The strategy is evaluating the similar characteristics that pose a common research path regarding challenges faced in real-world conditions. Additionally, this paper proposes a case study to assess the best input signals, metrics, and machine learning-based decision algorithms of a new HIFLM. The results are promising, with high identification rates, even in noisy conditions. The methodology can help to select the datasets for supervised learning-based HIFLM. Highlighting the state-of-art of current methods and support development of HIFLMs are this paper's main contributions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High Impedance Fault Location Methods: Review and Harmonic Selection-Based Analysis

Lopes

Menezes

Gomes

et al. 2023

IEEE Open J. Power Energy

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“…In 1949, the Power Systems Relaying Committee Working Group concluded that it was impossible at that time to develop techniques for detecting HIF [9]. However, especially in the last four decades, many researchers have been working to develop techniques that can detect, classify, and/or locate this type of fault [3], [6], [10], [11]. Despite the several studies presented in the literature, this research problem still lacks a definitive solution that presents high reliability and security in terms of detection and differentiation between the occurrence of HIF and other events common to distribution systems, such as switching loads or capacitors bank [6], [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Networks: Modeling and Comparison to Detect High Impedance Faults

Diefenthäler,

Sausen,

De Campos

et al. 2023

IEEE Access

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High impedance faults constitute one of the biggest challenges in electrical power systems. In overhead distribution systems, faults are caused by tree branches that touch the electrical grid or by the rupture of energized conductors on low conductivity soils. They are also known as low-current faults, which are not detected by conventional protection systems, compromising the quality of the power supply and causing hazardous risks to the electrical system. This paper aims to address the problem of high impedance faults detection using Artificial Neural Networks: two Multi Layer Perceptron networks, being one Neural Pattern Recognition and another Neural Fitting, and a Convolutional Neural Network. The neural networks are trained and analyzed in scenarios based on a medium-voltage distribution grid model, located in the Basque Country, Spain. The network topologies are implemented, repeatedly trained considering multiple architectures, and validated in other scenarios with different location, time, and duration of the fault using the Matlab software. After, the criteria of accuracy, reliability, security, safety and sensitivity are evaluated. At last, a comparative analysis between them is carried out, and from the results obtained, a superior performance of the Convolutional Neural Network in compared to the Multi Layer Perceptron networks is observed.

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“…Another example is power line communication (PLC) device which continually monitors the feeder impedance and detects the fault when an abrupt change in the high frequency impedance is asserted. This falls short of reliability test due to the fact that it requires knowledge of the impedance and resonant frequencies of the system for the best narrow frequency range selection (Gomes and Ozansoy, 2020). The method of high impedance fault detection is generally categorized into mechanical and electrical detection techniques.…”

Section: Introductionmentioning

confidence: 99%

High impedance fault arc analysis on 11 kV distribution networks

A.I.¹,

Amako²,

Ezeonye³

2022

Nig. J. Technol. Dev.

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This paper presents a study of high impedance fault (HIF) arc analysis on 6 km 11 kV distribution network from New Haven to New NNPC, Enugu State. These HIF currents have low fault current ratings and are not readily detected by the distribution sub-station relays and protective equipment. This was realized with the aid of MATLAB. Firstly, the HIF was modelled based on the electric arc theory method for single line-to-ground and double line-to-ground faults, when the 11 kV New-haven to New NNPC Enugu distribution line interfaces with a dry asphalt ground surface. The HIF was incident on the midpoint of the distribution line between the switching times of the circuit breaker from 0.02 to 0.05 seconds. The results showed that for single line-to-ground and double line-to-ground faults, a peak current magnitude of 12.4 A and 2280 A were seen respectively and initial spikes due to arcing in the system voltages at the initial switching times of 0.02 seconds. The corresponding residual currents Ib and Ic are very small with a peak spike of 0.3 A and 1.9 A for double line-to-ground fault (BC-G). These spikes are because of the impact of the initial transients caused by the arc flames as its quenches and re-ignites.

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High-impedance faults in power distribution systems: A narrative of the field’s developments

Cited by 19 publications

References 77 publications

High Impedance Fault Location Methods: Review and Harmonic Selection-Based Analysis

High Impedance Fault Location Methods: Review and Harmonic Selection-Based Analysis

Artificial Neural Networks: Modeling and Comparison to Detect High Impedance Faults

High impedance fault arc analysis on 11 kV distribution networks

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