Low Cost Arc Fault Detection and Protection for PV Systems: January 30, 2012 - September 30, 2013

McCalmont, Scott

doi:10.2172/1110454

Cited by 10 publications

(2 citation statements)

References 1 publication

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“…Salah satu jenis dari ganguan arc fault adalah series arc fault. Dalam pengaplikasian sistem microgrid, series arc fault lebih sering terjadi akibat kegagalan kontinuitas yang seharusnya ada pada sebuah konduktor atau konektor dalam rangkaian listrik [8].…”

Section: Pendahuluanunclassified

Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid

Anggriawan,

Sunarno,

Sunarno

et al. 2023

JTT (Jurnal Teknologi Terpadu)

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A microgrid is a cluster of electrical sources and loads that are interconnected and synchronized. Microgrid operation is typically divided into two modes, isolated or connected to the grid with a single or standalone control system. In this context, it can enhance the reliability and quality of electricity supply for connected customers. When using a microgrid system, it is important to consider the risk of series arc faults. Series arc faults are sudden bursts of flames resulting from ionization of gas between two electrode gaps. These faults can occur due to manufacturing defects, installation Errors, aging, or corrosion on conductor rods, leading to imperfect connections. Detecting series arc faults in DC microgrid system operations can be challenging using standard protective devices. Failure in the protection system can pose risks of fire, electrical shock hazards, and power loss in the DC microgrid.Therefore, a device has been designed to detect series arc faults by utilizing the fast Fourier transform method and artificial neural network, which function to analyze DC signal and make decisions when faults occur by examining the average sum of current frequency values during normal and fault conditions. In this study, the average sum of current frequency values during normal conditions was found to range from 0.35437 to 0.36906 A, while during fault conditions, it ranged from 0.21450 to 0.22793 A, with an average protection identification time of 1087 ms and an ANN output accuracy of 99.98%.

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Section: Pendahuluanunclassified

Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid

Anggriawan,

Sunarno,

Sunarno

et al. 2023

JTT (Jurnal Teknologi Terpadu)

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“…While the Gaussian function describes the probability distribution related to the value, the "colour" indicates the signal power distribution over a wide frequency range. It was generally assumed that the random noise of a DC arc was either a pink or Brownian noise [35]. Specifically, the development of the pink noise frequently occurs through the filtering of the Gaussian white noise.…”

Section: Bmentioning

confidence: 99%

Models, Detection Methods, and Challenges in Dc Arc Fault: A Review

et al. 2021

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The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is signiﬁcantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identiﬁcation, diagnosis, and interruption tools. Meanwhile, the faults in unidentiﬁed arc lead to serious ﬁre hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such hazards is crucial in the early phases of the distribution. In this paper, a detailed review of modern approaches for the identiﬁcation of DC arc faults in PV is presented. In addition, a thorough comparison is performed between various DC arc-fault models, characteristics, and approaches used for the identiﬁcation of the faults.

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Newly-Designed DC-Arc Fault Detection Strategy Via EMD Signal Analysis and GRU Neural Network for Solar PV Power Generation System

Wai,

Cai

2023

2023 5th International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

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Low Cost Arc Fault Detection and Protection for PV Systems: January 30, 2012 - September 30, 2013

Cited by 10 publications

References 1 publication

Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid

Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid

Models, Detection Methods, and Challenges in Dc Arc Fault: A Review

Newly-Designed DC-Arc Fault Detection Strategy Via EMD Signal Analysis and GRU Neural Network for Solar PV Power Generation System

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