DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique
This paper proposes a DC series arc detection algorithm in a photovoltaic (PV) system using an adaptive moving average (AMA). The proposed algorithm uses two moving averages of <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula> which i...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9469873/ |
| _version_ | 1818671340879609856 |
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| author | Jaechang Kim Sangshin Kwak Seungdeog Choi |
| author_facet | Jaechang Kim Sangshin Kwak Seungdeog Choi |
| author_sort | Jaechang Kim |
| collection | DOAJ |
| description | This paper proposes a DC series arc detection algorithm in a photovoltaic (PV) system using an adaptive moving average (AMA). The proposed algorithm uses two moving averages of <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula> which is the average of 5 kHz to 40 kHz frequency band. One is <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula> which is the moving average highly affected by recent <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula>. The other is <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> which is the moving average heavily affected by past <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula>. There is a little difference between <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> before arcing because <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula> is approximately constant. However, this difference increases when the arc occurs because <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> slowly follows <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula>. This difference is used as an arc detection indicator (ADI) in this study. Additionally, AMA is proposed to avoid nuisance tripping in the normal transient state. The proposed method determines the arc occurrence using the relative magnitudes of the two moving averages. Therefore, it is less affected by the shape of the frequency fluctuations caused by the load inverter. Hence, the proposed algorithm is effective in the centralized and spread-type of frequency fluctuations. These results were verified through an arc detection test and nuisance tripping test using arc experimental data and MATLAB. |
| first_indexed | 2024-12-17T07:22:27Z |
| format | Article |
| id | doaj.art-614ebc5830324a6b8a91fdec74dd3e08 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T07:22:27Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-614ebc5830324a6b8a91fdec74dd3e082022-12-21T21:58:43ZengIEEEIEEE Access2169-35362021-01-019944269443710.1109/ACCESS.2021.30939809469873DC Series Arc Detection Algorithm Based on Adaptive Moving Average TechniqueJaechang Kim0https://orcid.org/0000-0002-0645-1414Sangshin Kwak1https://orcid.org/0000-0002-2890-906XSeungdeog Choi2https://orcid.org/0000-0002-7549-6093School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaDepartment of Electrical and Computer Engineering, Mississipi State University, Starkville, MS, USAThis paper proposes a DC series arc detection algorithm in a photovoltaic (PV) system using an adaptive moving average (AMA). The proposed algorithm uses two moving averages of <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula> which is the average of 5 kHz to 40 kHz frequency band. One is <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula> which is the moving average highly affected by recent <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula>. The other is <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> which is the moving average heavily affected by past <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula>. There is a little difference between <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> before arcing because <inline-formula> <tex-math notation="LaTeX">$F_{av}$ </tex-math></inline-formula> is approximately constant. However, this difference increases when the arc occurs because <inline-formula> <tex-math notation="LaTeX">${MA}_{large}$ </tex-math></inline-formula> slowly follows <inline-formula> <tex-math notation="LaTeX">${MA}_{small}$ </tex-math></inline-formula>. This difference is used as an arc detection indicator (ADI) in this study. Additionally, AMA is proposed to avoid nuisance tripping in the normal transient state. The proposed method determines the arc occurrence using the relative magnitudes of the two moving averages. Therefore, it is less affected by the shape of the frequency fluctuations caused by the load inverter. Hence, the proposed algorithm is effective in the centralized and spread-type of frequency fluctuations. These results were verified through an arc detection test and nuisance tripping test using arc experimental data and MATLAB.https://ieeexplore.ieee.org/document/9469873/DC series arcmoving averagefrequency fluctuations |
| spellingShingle | Jaechang Kim Sangshin Kwak Seungdeog Choi DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique IEEE Access DC series arc moving average frequency fluctuations |
| title | DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique |
| title_full | DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique |
| title_fullStr | DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique |
| title_full_unstemmed | DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique |
| title_short | DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique |
| title_sort | dc series arc detection algorithm based on adaptive moving average technique |
| topic | DC series arc moving average frequency fluctuations |
| url | https://ieeexplore.ieee.org/document/9469873/ |
| work_keys_str_mv | AT jaechangkim dcseriesarcdetectionalgorithmbasedonadaptivemovingaveragetechnique AT sangshinkwak dcseriesarcdetectionalgorithmbasedonadaptivemovingaveragetechnique AT seungdeogchoi dcseriesarcdetectionalgorithmbasedonadaptivemovingaveragetechnique |