Fault Detection and Fault Diagnosis in Power System Using AI: A Review
Electricity, which is essential to modern society, necessitates a consistent and uninterrupted supply. Faults in power systems pose difficulties, highlighting the vital importance of fault identification and diagnosis. This review paper provides a concise overview of artificial intelligence-based f...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Sir Syed University of Engineering and Technology, Karachi.
2024-04-01
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| Series: | Sir Syed University Research Journal of Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/598 |
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| author | syeda Faiza Nasim Sidra Aziz Asma Qaiser Umme Kulsoom Saad Ahmed |
| author_facet | syeda Faiza Nasim Sidra Aziz Asma Qaiser Umme Kulsoom Saad Ahmed |
| author_sort | syeda Faiza Nasim |
| collection | DOAJ |
| description |
Electricity, which is essential to modern society, necessitates a consistent and uninterrupted supply. Faults in power systems pose difficulties, highlighting the vital importance of fault identification and diagnosis. This review paper provides a concise overview of artificial intelligence-based fault detection and diagnosis in power systems. The primary focus is on deep learning; on the one hand, it compares
various works and acts as a primer for those who are unfamiliar with them. On the other hand, it delves into the application of UV-visible video processing to detect incipient faults by analyzing corona discharge and air ionization. Moreover, this state-of-the-art work highlights deep learning applications, particularly in UV-visible video processing, with the goal of detecting incipient faults through corona discharge and air ionization analysis. Despite ongoing research, the field lacks a clear path and structure, emphasizing the need for continued advancement in utilizing AI for effective fault detection and diagnosis in power systems.
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| format | Article |
| id | doaj-art-2f2cb610271546009cb7a32ca1bbe816 |
| institution | Kabale University |
| issn | 1997-0641 2415-2048 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | Sir Syed University of Engineering and Technology, Karachi. |
| record_format | Article |
| series | Sir Syed University Research Journal of Engineering and Technology |
| spelling | doaj-art-2f2cb610271546009cb7a32ca1bbe8162025-08-20T03:26:52ZengSir Syed University of Engineering and Technology, Karachi.Sir Syed University Research Journal of Engineering and Technology1997-06412415-20482024-04-0114110.33317/ssurj.598Fault Detection and Fault Diagnosis in Power System Using AI: A Reviewsyeda Faiza Nasim0Sidra Aziz1Asma Qaiser2Umme Kulsoom3Saad Ahmed4NED universityAligarh InstituteIqra UniversityPaf -KietIqra University Electricity, which is essential to modern society, necessitates a consistent and uninterrupted supply. Faults in power systems pose difficulties, highlighting the vital importance of fault identification and diagnosis. This review paper provides a concise overview of artificial intelligence-based fault detection and diagnosis in power systems. The primary focus is on deep learning; on the one hand, it compares various works and acts as a primer for those who are unfamiliar with them. On the other hand, it delves into the application of UV-visible video processing to detect incipient faults by analyzing corona discharge and air ionization. Moreover, this state-of-the-art work highlights deep learning applications, particularly in UV-visible video processing, with the goal of detecting incipient faults through corona discharge and air ionization analysis. Despite ongoing research, the field lacks a clear path and structure, emphasizing the need for continued advancement in utilizing AI for effective fault detection and diagnosis in power systems. http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/598Artificial IntelligenceComputing MachinesFault DetectionFault DiagnosisElectrical Power System |
| spellingShingle | syeda Faiza Nasim Sidra Aziz Asma Qaiser Umme Kulsoom Saad Ahmed Fault Detection and Fault Diagnosis in Power System Using AI: A Review Sir Syed University Research Journal of Engineering and Technology Artificial Intelligence Computing Machines Fault Detection Fault Diagnosis Electrical Power System |
| title | Fault Detection and Fault Diagnosis in Power System Using AI: A Review |
| title_full | Fault Detection and Fault Diagnosis in Power System Using AI: A Review |
| title_fullStr | Fault Detection and Fault Diagnosis in Power System Using AI: A Review |
| title_full_unstemmed | Fault Detection and Fault Diagnosis in Power System Using AI: A Review |
| title_short | Fault Detection and Fault Diagnosis in Power System Using AI: A Review |
| title_sort | fault detection and fault diagnosis in power system using ai a review |
| topic | Artificial Intelligence Computing Machines Fault Detection Fault Diagnosis Electrical Power System |
| url | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/598 |
| work_keys_str_mv | AT syedafaizanasim faultdetectionandfaultdiagnosisinpowersystemusingaiareview AT sidraaziz faultdetectionandfaultdiagnosisinpowersystemusingaiareview AT asmaqaiser faultdetectionandfaultdiagnosisinpowersystemusingaiareview AT ummekulsoom faultdetectionandfaultdiagnosisinpowersystemusingaiareview AT saadahmed faultdetectionandfaultdiagnosisinpowersystemusingaiareview |