Search results for "Arc fault"
showing 10 items of 13 documents
Characterization of DC series arc faults in PV systems based on current low frequency spectral analysis
2021
Abstract This work presents an experimental study focused on the characterization of series arc faults in direct current (DC) photovoltaic (PV) systems. The aim of the study is to identify some relevant characteristics of arcing current, which can be obtained by means of low frequency spectral analysis of current signal. On field tests have been carried out on a real PV system, in accordance with some tests requirements of UL 1699B Standard for protection devices against PV DC arc faults. Arcing and non-arcing current signals are acquired and compared and the behavior of a set of indicators proposed by authors is analyzed. Different measurement equipment have been used, in order to study th…
Fractal Dimension Logarithmic Differences Method for Low Voltage Series Arc Fault Detection
2021
Series arc faults introduce singularities in the current signal and changes over time. Fractal dimension can be used to characterize the dynamic behaviour of the current signal by providing a degree of signal chaos. This measure of irregularity exhibits changes in signal behaviour that can suitably be used as a basis for series arc fault detection. In this paper, an efficient low voltage series arc fault detection method based on the logarithmic differences of the estimate of the fractal dimension of the current signal using the multiresolution length-based method is presented. The discrete wavelet transform and the hard thresholding denoising with the universal threshold are also used. Exp…
Study, project and implementation of new metrics for distributed measurement system in medium voltage smart grid
2022
A set of indicators for arc faults detection based on low frequency harmonic analysis
2016
In this paper a novel set of indicators is presented for arc faults detection in electrical circuits. The indicators are defined starting from an experimental characterization of the arc fault phenomenon and the study of the arcing current in several test conditions, which were chosen in accordance with the UL 1699 Standard requirements. The proposed parameters are measured by means of a high resolution low frequency spectral analysis of the arcing current, which allows to achieve a good spectral resolution even with short observation windows.
Arc Fault Detection Method Based on CZT Low-Frequency Harmonic Current Analysis
2017
This paper presents a method for the detection of series arc faults in electrical circuits, which has been developed starting from an experimental characterization of the arc fault phenomenon and an arcing current study in several test conditions. Starting from this, the authors have found that is it possible to suitably detect arc faults by means of a high-resolution low-frequency harmonic analysis of current signal, based on chirp zeta transform, and a proper set of indicators. The proposed method effectiveness is shown by means of experimental tests, which were carried in both arcing and nonarcing conditions and in the presence of different loads, chosen according to the UL 1699 standard…
Experimental characterization of series arc faults in AC and DC electrical circuits
2014
This paper presents an experimental characterization of the arc fault phenomenon, for both AC and DC systems, focusing the attention on series arcs. The aim of the study is to find some current characteristics, which can be significant for the purpose of arc detection. The arcing current signal is analyzed in both time and frequency domain. For the AC analysis, the test conditions are chosen in accordance with the “unwanted tripping tests” and the “operation inhibition tests” reported in the Standard UL 1699. The DC study is carried out on the currents waveforms acquired during some on-field tests on a PV plant. Starting from the study herein presented, the authors have found that is it pos…
DC series arc faults in PV systems. Detection methods and experimental characterization
2020
This work is focused on the arc faults phenomenon in DC photovoltaic (PV) systems. The paper gives an overview of arc detection methods proposed in literature and presents a preliminary experimental characterization of the arcing current, focusing the attention on series arcs, whose detection is particularly challenging. Experimental tests are carried out, both in laboratory and on field, in order to investigate some relevant characteristics in the arcing current, which can be feasible for the arc detection purpose. Both arcing and non-arcing current signals are acquired and compared in both time and frequency domain. On-field measurements are carried out on a real photovoltaic system, in a…
A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault
2020
This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.
ARC FAULT DETECTION EQUIPMENT AND METHOD USING LOW FREQUENCY HARMONIC CURRENT ANALYSIS
2012
An arc fault detection circuit includes a current sensing circuit coupled to a line conductor carrying a current. The current sensing circuit operates to sense current and output data indicative of the sensed current. A processing circuit implements a frequency transform algorithm to transform the output data to frequency data in a low frequency range and with a high spectral resolution where a minimum short time observation window is concerned. The processing circuit identifies an arc fault condition on the line conductor by identifying differences in said frequency data between at least two subsequent observation windows and identifying characteristics which exceed thresholds.