Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique
Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques c...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/9674054 |
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| author | Edwell T. Mharakurwa G. N. Nyakoe A. O. Akumu |
| author_facet | Edwell T. Mharakurwa G. N. Nyakoe A. O. Akumu |
| author_sort | Edwell T. Mharakurwa |
| collection | DOAJ |
| description | Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers. |
| format | Article |
| id | doaj-art-bc7e5796fb54415998bc0a207201def8 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-bc7e5796fb54415998bc0a207201def82025-02-03T05:49:41ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552019-01-01201910.1155/2019/96740549674054Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation TechniqueEdwell T. Mharakurwa0G. N. Nyakoe1A. O. Akumu2Department of Electrical Engineering, Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), P.O. Box 62000-00200, City Square, Nairobi, KenyaDepartment of Electrical Engineering, Jomo Kenyatta University of Agriculture and Technology (JKUAT), P.O. Box 62000-00200, City Square, Nairobi, KenyaDepartment of Electrical Engineering, Tshwane University of Technology (TUT), Private Bag X680 0001, Pretoria, South AfricaDecision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers.http://dx.doi.org/10.1155/2019/9674054 |
| spellingShingle | Edwell T. Mharakurwa G. N. Nyakoe A. O. Akumu Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique Journal of Electrical and Computer Engineering |
| title | Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique |
| title_full | Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique |
| title_fullStr | Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique |
| title_full_unstemmed | Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique |
| title_short | Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique |
| title_sort | power transformer fault severity estimation based on dissolved gas analysis and energy of fault formation technique |
| url | http://dx.doi.org/10.1155/2019/9674054 |
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