AI in arcing-HIF detection: a brief review
In the past few decades, the arcing-high-impedance fault (arcing-HIF) detection problems have become an important issue in the effectively grounded distribution network. Many solutions have been proposed to address this problem. The most attractive way is artificial intelligence (AI) method. The pap...
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| Format: | Article |
| Language: | English |
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Wiley
2020-02-01
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| Series: | IET Smart Grid |
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| Online Access: | https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0091 |
| _version_ | 1818730223896625152 |
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| author | Bai Hao |
| author_facet | Bai Hao |
| author_sort | Bai Hao |
| collection | DOAJ |
| description | In the past few decades, the arcing-high-impedance fault (arcing-HIF) detection problems have become an important issue in the effectively grounded distribution network. Many solutions have been proposed to address this problem. The most attractive way is artificial intelligence (AI) method. The paper gives a comprehensive review of arcing-HIF detection in distribution network-based AI. First, characteristics and models of arcing-HIF are analysed, the arcing-HIF database construction method is also explained; this part is a foundation work for arcing-HIF detection. Next, arcing-HIF detection methods based AI are summarised in details including data acquisition, feature extraction and classifier selection. Then, a set of criteria are proposed to evaluate the reliability of arcing-HIF detection algorithm. Finally, the future trends and challenges to arcing-HIF detection are also fully accounted. This review can be a valuable guide for researchers who are interested in arcing-HIF detection-based AI. |
| first_indexed | 2024-12-17T22:58:22Z |
| format | Article |
| id | doaj.art-05bf54c9854243c49cd87e8a54e679f8 |
| institution | Directory Open Access Journal |
| issn | 2515-2947 |
| language | English |
| last_indexed | 2024-12-17T22:58:22Z |
| publishDate | 2020-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Smart Grid |
| spelling | doaj.art-05bf54c9854243c49cd87e8a54e679f82022-12-21T21:29:28ZengWileyIET Smart Grid2515-29472020-02-0110.1049/iet-stg.2019.0091IET-STG.2019.0091AI in arcing-HIF detection: a brief reviewBai Hao0Power Distribution Technology Department, Electric Power Research Institute of China Southern Power GridIn the past few decades, the arcing-high-impedance fault (arcing-HIF) detection problems have become an important issue in the effectively grounded distribution network. Many solutions have been proposed to address this problem. The most attractive way is artificial intelligence (AI) method. The paper gives a comprehensive review of arcing-HIF detection in distribution network-based AI. First, characteristics and models of arcing-HIF are analysed, the arcing-HIF database construction method is also explained; this part is a foundation work for arcing-HIF detection. Next, arcing-HIF detection methods based AI are summarised in details including data acquisition, feature extraction and classifier selection. Then, a set of criteria are proposed to evaluate the reliability of arcing-HIF detection algorithm. Finally, the future trends and challenges to arcing-HIF detection are also fully accounted. This review can be a valuable guide for researchers who are interested in arcing-HIF detection-based AI.https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0091artificial intelligencepower distribution faultsfault diagnosisarcs (electric)power distribution reliabilitypower engineering computingarcing-high-impedance fault detection problemsarcing-hif database construction methodarcing-hif detection-based ai algorithmdistribution network-based ai algorithmgrounded distribution networkartificial intelligence methoddata acquisitionfeature extractionclassifier selectionreliability |
| spellingShingle | Bai Hao AI in arcing-HIF detection: a brief review IET Smart Grid artificial intelligence power distribution faults fault diagnosis arcs (electric) power distribution reliability power engineering computing arcing-high-impedance fault detection problems arcing-hif database construction method arcing-hif detection-based ai algorithm distribution network-based ai algorithm grounded distribution network artificial intelligence method data acquisition feature extraction classifier selection reliability |
| title | AI in arcing-HIF detection: a brief review |
| title_full | AI in arcing-HIF detection: a brief review |
| title_fullStr | AI in arcing-HIF detection: a brief review |
| title_full_unstemmed | AI in arcing-HIF detection: a brief review |
| title_short | AI in arcing-HIF detection: a brief review |
| title_sort | ai in arcing hif detection a brief review |
| topic | artificial intelligence power distribution faults fault diagnosis arcs (electric) power distribution reliability power engineering computing arcing-high-impedance fault detection problems arcing-hif database construction method arcing-hif detection-based ai algorithm distribution network-based ai algorithm grounded distribution network artificial intelligence method data acquisition feature extraction classifier selection reliability |
| url | https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0091 |
| work_keys_str_mv | AT baihao aiinarcinghifdetectionabriefreview |