Ali, Mohd Syukri and Bakar, Ab Halim Abu and Omar, Azimah and Jaafar, Amirul Syafiq Abdul and Mohamed, Siti Hajar (2023) Conventional methods of dissolved gas analysis using oil-immersed power transformer for fault diagnosis: A review. Electric Power Systems Research, 216. ISSN 0378-7796, DOI https://doi.org/10.1016/j.epsr.2022.109064.
Full text not available from this repository.Abstract
This review paper summarizes the discoveries made about dissolved gas analysis (DGA) conventional methods around the decade. DGA is a well-known diagnostic tool to classify different fault types that are likely to occur in oil-filled transformers. Interpretation methods for fault detection include the Key Gases Method, Duval Triangle Method, Duval Pentagon Method, and Ratio Methods consisting of the IEC Method, Rogers Method, and Doer-nenburg Method. In this review paper, a brief introduction of DGA will be given, followed by a review of each method, and the correlation of fault types between methods has also been reviewed so that the readers have a clear view of the capability of each method. The paper highlights the merits and demerits of each method that can be guided before selecting the most suitable DGA method for performing the diagnostic analysis. In this regard, it is of utmost importance to enhance the reliability and accuracy of each DGA method in the diagnostic process, since it detects early transformer faults, and therefore prevents further damage to the specific trans-former. Finally, the conclusion and future works on this topic also will be presented accordingly.
Item Type: | Article |
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Funders: | UM International Collaboration Grant, SATU Joint Research Scheme Program (ST033-2022) |
Uncontrolled Keywords: | Transformer monitoring; Incipient faults; Fault detection; Dissolved gas concentration |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Deputy Vice Chancellor (Research & Innovation) Office > UM Power Energy Dedicated Advanced Centre |
Depositing User: | Ms Zaharah Ramly |
Date Deposited: | 22 Nov 2023 06:51 |
Last Modified: | 22 Nov 2023 06:51 |
URI: | http://eprints.um.edu.my/id/eprint/39220 |
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