A Series DC Arc Fault Detection Method Based on Steady Pattern of High-Frequency Electromagnetic Radiation
| Autor: | Youxin Xu, Yao Wang, Kui Li, Chen Zhu, Feng Niu, Shuangle Zhao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Nuclear and High Energy Physics
Computer science Photovoltaic system Bandwidth (signal processing) Arc-fault circuit interrupter Condensed Matter Physics 01 natural sciences Electromagnetic radiation Fault detection and isolation 010305 fluids & plasmas Electric power system Control theory Frequency domain 0103 physical sciences Spectrogram |
| Zdroj: | IEEE Transactions on Plasma Science. 47:4370-4377 |
| ISSN: | 1939-9375 0093-3813 |
| DOI: | 10.1109/tps.2019.2932747 |
| Popis: | Due to detection difficulties, dc arc faults are one of the most dangerous risks in dc power systems. Most traditional studies are based on arc current, which may change during normal operation and cause unwanted trips. Another problem with the traditional methods is that the detection threshold may need to be adjusted for different photovoltaic (PV) systems; otherwise, it will cause malfunctions. To solve the aforementioned problems, a series arc fault detection method based on steady patterns of the frequency domain is proposed. The proposed method utilizes the electromagnetic radiation (EMR) emitted by an arc as a testing basis, avoiding the occurrence of unwanted trips. Patterns such as the structural similarity index (SSIM) and 6-dB bandwidth bins (6-dB BWBs) are calculated to extract the similarity of the steady-burning arc spectra. The experimental verification shows that the proposed steady-pattern-based method can accurately identify arc faults in different dc power systems, discriminate arc faults from normal operations, effectively avoid the occurrence of malfunctions, and can be used as a supplementary technique to traditional methods. |
| Databáze: | OpenAIRE |
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