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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM17525
Volume:
7 |
1 |
Jan 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Power transformer malfunctions cause significant power outages and, as a result, material damage. This critical issue must be resolved. Power transformers must be protected from various fault conditions and power system failure. Fuzzy logic is used in this study to detect and protect power system transformer faults. In the simulation system that diagnoses transformer faults and monitors its operating conditions, the fuzzy logic (FL) toolbox in MATLAB/ SIMULINK software was used. The input variables, current and rate of change of current with time, have been identified as “Error” and “Error-Dot” in the programme. The study’s findings show that when the output response is zero, the current in the transformer is normal. This is obtained by injecting [0] and [0] input values into the system, resulting in a response of “6e(-017),” which is close to zero. If the output response is greater than zero, the transformer current is rising above normal and the protection scheme should be notified. This condition is achieved by giving the system input values of [-1.5] and [5] and expecting a response of “+5”. If the response is less than zero, the transformer current is less than normal, and the protection scheme should be notified. The study concluded that electrical faults and mechanical failures in power transformers can be quickly identified using Fuzzy logic. Thus, power transformer damage is avoided by controlling relays more effectively and quickly. This has resulted in significant savings in maintenance and repair costs. It is assumed that the study was a success.
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Publication Date
1/19/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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