A DC arc detection method for photovoltaic (PV) systems
PV arc-faults can cause fires, damage property, and endanger people's lives. This paper proposes a method for detecting DC arcs using artificial intelligence (AI). The four steps for arc detection are thoroughly described. After removing the low-frequency range (41 kHz) and high-frequency range...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024000604 |
| _version_ | 1827310623587827712 |
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| author | Wenping Zhang Po Xu Yiming Wang Donghui Li Baosong Liu |
| author_facet | Wenping Zhang Po Xu Yiming Wang Donghui Li Baosong Liu |
| author_sort | Wenping Zhang |
| collection | DOAJ |
| description | PV arc-faults can cause fires, damage property, and endanger people's lives. This paper proposes a method for detecting DC arcs using artificial intelligence (AI). The four steps for arc detection are thoroughly described. After removing the low-frequency range (41 kHz) and high-frequency range (>102.5 kHz) components, the middle frequency range is left for arc analysis. For AI analysis, eight inputs are used. The time sequence for the tasks is also explained, where the parallel task configuration is adopted to save the time. Furthermore, AI model training for arc detection is described, including both offline and online training. In addition, three different types of arc detection system architectures are depicted. There are three layers in the architectures: the PV-end layer, the inverter-level layer, and the cloud layer. Depending on the architecture, the algorithm is located in different layers. Furthermore, the hardware of the arc detection system is explained, as is the self-testing circuit. Finally, an experimental platform is built, and experimental results are presented to validate the proposed method. |
| first_indexed | 2024-03-08T12:08:19Z |
| format | Article |
| id | doaj.art-0800eb982e5d4ab691c9e2456742b827 |
| institution | Directory Open Access Journal |
| issn | 2590-1230 |
| language | English |
| last_indexed | 2024-04-24T20:03:06Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj.art-0800eb982e5d4ab691c9e2456742b8272024-03-24T07:00:44ZengElsevierResults in Engineering2590-12302024-03-0121101807A DC arc detection method for photovoltaic (PV) systemsWenping Zhang0Po Xu1Yiming Wang2Donghui Li3Baosong Liu4Tianjin University, 92 Weijin Road Nankai District, Tianjin, 300072, China; Ginlong Technologies Co., Ltd., 57 Jintong Road, Xiangshan, Ningbo, 315712, China; Corresponding author. Ginlong Technologies Co., Ltd., 57 Jintong Road, Xiangshan, Ningbo, 315712, China.Ginlong Technologies Co., Ltd., 57 Jintong Road, Xiangshan, Ningbo, 315712, ChinaGinlong Technologies Co., Ltd., 57 Jintong Road, Xiangshan, Ningbo, 315712, ChinaTianjin University, 92 Weijin Road Nankai District, Tianjin, 300072, ChinaGinlong Technologies Co., Ltd., 57 Jintong Road, Xiangshan, Ningbo, 315712, ChinaPV arc-faults can cause fires, damage property, and endanger people's lives. This paper proposes a method for detecting DC arcs using artificial intelligence (AI). The four steps for arc detection are thoroughly described. After removing the low-frequency range (41 kHz) and high-frequency range (>102.5 kHz) components, the middle frequency range is left for arc analysis. For AI analysis, eight inputs are used. The time sequence for the tasks is also explained, where the parallel task configuration is adopted to save the time. Furthermore, AI model training for arc detection is described, including both offline and online training. In addition, three different types of arc detection system architectures are depicted. There are three layers in the architectures: the PV-end layer, the inverter-level layer, and the cloud layer. Depending on the architecture, the algorithm is located in different layers. Furthermore, the hardware of the arc detection system is explained, as is the self-testing circuit. Finally, an experimental platform is built, and experimental results are presented to validate the proposed method.http://www.sciencedirect.com/science/article/pii/S2590123024000604PVArc detectionDC/DCAI |
| spellingShingle | Wenping Zhang Po Xu Yiming Wang Donghui Li Baosong Liu A DC arc detection method for photovoltaic (PV) systems Results in Engineering PV Arc detection DC/DC AI |
| title | A DC arc detection method for photovoltaic (PV) systems |
| title_full | A DC arc detection method for photovoltaic (PV) systems |
| title_fullStr | A DC arc detection method for photovoltaic (PV) systems |
| title_full_unstemmed | A DC arc detection method for photovoltaic (PV) systems |
| title_short | A DC arc detection method for photovoltaic (PV) systems |
| title_sort | dc arc detection method for photovoltaic pv systems |
| topic | PV Arc detection DC/DC AI |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024000604 |
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