LAPSE:2023.26404
Published Article

LAPSE:2023.26404
Application of Dissolved Gas Analysis in Assessing Degree of Healthiness or Faultiness with Fault Identification in Oil-Immersed Equipment
April 3, 2023
Abstract
The healthiness and or faultiness of oil-immersed electrical equipment using dissolved gas characterization has remained a critical and challenging task in power systems. Dissolved gas analysis (DGA) continues to be the utmost preferred technique of detecting mainly slow evolving thermal and electrical faults. However, DGA can reveal more than just faults in equipment. This research looks at broad areas where DGA can be applied to determine the healthiness or faultiness of equipment in addition to fault identification. In equipment considered normal—i.e., fault-free—DGA can give the degree of healthiness (DOH) based on Rogers ratios C2H2/C2H4 < 0.1, 0.1 < CH4/H2 < 1, and C2H4/C2H6 < 1, plus the 3 < CO2/CO < 10 ratio for identifying fault-free devices. This answers the question: How healthy or normal is the equipment? Similarly, when these ratios are violated, it signifies the presence of faults, and two things ought to be determined. One is to identify the type of fault(s), which has been the norm. The other thing that can be evaluated is the degree of faultiness (DOF), based on the extent to which the ratios have been violated. Rarely has this been done. This might answer the question for the same fault class: How severe is the fault? To synthesize the DOH and/or DOF, fuzzy logic is applied. To diagnose faults, fuzzy logic and fuzzy-evidential tools are proposed. The accuracy and effectiveness of the proposed fuzzy techniques are better than those of the IEC60599 and Rogers methods, and they are comparable to those of the Duval Triangle 1 and Pentagon 1 methods using the six IEC faults. Results from DOF evaluation have shown electrical faults to be more impactful relative to the rest.
The healthiness and or faultiness of oil-immersed electrical equipment using dissolved gas characterization has remained a critical and challenging task in power systems. Dissolved gas analysis (DGA) continues to be the utmost preferred technique of detecting mainly slow evolving thermal and electrical faults. However, DGA can reveal more than just faults in equipment. This research looks at broad areas where DGA can be applied to determine the healthiness or faultiness of equipment in addition to fault identification. In equipment considered normal—i.e., fault-free—DGA can give the degree of healthiness (DOH) based on Rogers ratios C2H2/C2H4 < 0.1, 0.1 < CH4/H2 < 1, and C2H4/C2H6 < 1, plus the 3 < CO2/CO < 10 ratio for identifying fault-free devices. This answers the question: How healthy or normal is the equipment? Similarly, when these ratios are violated, it signifies the presence of faults, and two things ought to be determined. One is to identify the type of fault(s), which has been the norm. The other thing that can be evaluated is the degree of faultiness (DOF), based on the extent to which the ratios have been violated. Rarely has this been done. This might answer the question for the same fault class: How severe is the fault? To synthesize the DOH and/or DOF, fuzzy logic is applied. To diagnose faults, fuzzy logic and fuzzy-evidential tools are proposed. The accuracy and effectiveness of the proposed fuzzy techniques are better than those of the IEC60599 and Rogers methods, and they are comparable to those of the Duval Triangle 1 and Pentagon 1 methods using the six IEC faults. Results from DOF evaluation have shown electrical faults to be more impactful relative to the rest.
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Keywords
degree of faultiness (DOF), degree of healthiness (DOH), dissolved gas analysis (DGA), evidential reasoning criterion, fault diagnosis, fuzzy characterization curves, fuzzy logic (FL), probability value assignments (PVAs)
Subject
Suggested Citation
Irungu GK, Akumu AO. Application of Dissolved Gas Analysis in Assessing Degree of Healthiness or Faultiness with Fault Identification in Oil-Immersed Equipment. (2023). LAPSE:2023.26404
Author Affiliations
Journal Name
Energies
Volume
13
Issue
18
Article Number
E4770
Year
2020
Publication Date
2020-09-12
ISSN
1996-1073
Version Comments
Original Submission
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PII: en13184770, Publication Type: Journal Article
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LAPSE:2023.26404
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https://doi.org/10.3390/en13184770
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Apr 3, 2023
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