DC Series Arc Fault Detection Algorithm for Distributed Energy Resources Using Arc Fault Impedance Modeling

Hwa-Pyeong Park,Suyong Chae

doi:10.1109/access.2020.3027869

Hwa-Pyeong Park, Suyong Chae

Open Access

https://doi.org/10.1109/access.2020.3027869

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Abstract

Arc fault detection is important technology to guarantee the safety of power systems and is therefore essential for producing practical power systems for real-world applications. However, fuses and arc fault detection devices (AFDD) struggle to detect series arc faults in DC systems, because the series arc fault induces small current variation between the normal and abnormal conditions. In addition, switching noise from the grid-connected inverter makes detecting arc fault conditions even more difficult. This paper proposes arc fault detection algorithm based on the relative comparison of current variability in terms of frequency spectrum and time series. The operational principle of the proposed algorithm is analyzed to detect the arc fault condition. In addition, the investigation of arc fault impedance using the small-signal modeling can obtain the resonant frequency of arc fault condition at low frequency range. From the impedance model, the frequency analysis range can be designed to avoid the switching noise of inverter. The performance of proposed arc fault detection algorithm is verified with a 3.8 kW grid-connected PV system and arc fault generator.

Highlights

The conventional grid system was developed based on power generation from fossil fuels, which is primary source of environmental pollution
This paper proposes the impedance model of arc fault condition under the low frequency range using the small signal modeling
In this paper, the arc fault detection algorithm is proposed with employing the time series and frequency spectrum analysis

Summary

INTRODUCTION

The conventional grid system was developed based on power generation from fossil fuels, which is primary source of environmental pollution. In [10], [14]– [16], time domain analysis was introduced to detect the arc fault condition, which uses current and voltage information. These methods provide fast detection speeds with simple circuits and algorithms, but they are susceptible to switching noise and load variation. In [17] and [18], frequency analysis was applied to detect the arc fault condition, which is based on the fast Fourier transform (FFT) or short time Fourier transform. The arc fault detection algorithm is proposed using the statistical analysis of arc current variability in terms of time and frequency domains.

IMPEDANCE ANALYSIS OF ARC FAULT

EXPERIMENTAL RESULTS

CONCLUSION