A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation
In determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. To increase the reliability of the faults’...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/4/1009 |
| _version_ | 1811213402303889408 |
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| author | Rahman Azis Prasojo Harry Gumilang Suwarno Nur Ulfa Maulidevi Bambang Anggoro Soedjarno |
| author_facet | Rahman Azis Prasojo Harry Gumilang Suwarno Nur Ulfa Maulidevi Bambang Anggoro Soedjarno |
| author_sort | Rahman Azis Prasojo |
| collection | DOAJ |
| description | In determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. To increase the reliability of the faults’ severity assessment of power transformers, a novel approach in the form of fuzzy logic has been proposed as a new solution to determine faults’ severity using the combination of gas level, gas rate, and DGA interpretation from the Duval Pentagon Method (DPM). A four-level typical concentration and rate were established based on the local population. To simplify the assessment of hundreds of power transformer data, a Support Vector Machine (SVM)-based DPM with high agreements to the graphical DPM has been developed. The proposed approach has been implemented to 448 power transformers and further implementation was done to evaluate faults’ severity of power transformers from historical DGA data. This new approach yields in high agreement with the previous methods, but with better sensitivity due to the incorporation of gas level, gas rate, and DGA interpretation results in one approach. |
| first_indexed | 2024-04-12T05:46:00Z |
| format | Article |
| id | doaj.art-28dd7b1150fd4571b3f3b20cc60dd26a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-12T05:46:00Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-28dd7b1150fd4571b3f3b20cc60dd26a2022-12-22T03:45:27ZengMDPI AGEnergies1996-10732020-02-01134100910.3390/en13041009en13041009A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis InterpretationRahman Azis Prasojo0Harry Gumilang1Suwarno2Nur Ulfa Maulidevi3Bambang Anggoro Soedjarno4School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung 40132, IndonesiaDepartment of Planning and Evaluation–UPT Bandung, PLN Unit Transmisi Jawa Bagian Tengah, Bandung 40255, IndonesiaSchool of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung 40132, IndonesiaSchool of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung 40132, IndonesiaSchool of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung 40132, IndonesiaIn determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. To increase the reliability of the faults’ severity assessment of power transformers, a novel approach in the form of fuzzy logic has been proposed as a new solution to determine faults’ severity using the combination of gas level, gas rate, and DGA interpretation from the Duval Pentagon Method (DPM). A four-level typical concentration and rate were established based on the local population. To simplify the assessment of hundreds of power transformer data, a Support Vector Machine (SVM)-based DPM with high agreements to the graphical DPM has been developed. The proposed approach has been implemented to 448 power transformers and further implementation was done to evaluate faults’ severity of power transformers from historical DGA data. This new approach yields in high agreement with the previous methods, but with better sensitivity due to the incorporation of gas level, gas rate, and DGA interpretation results in one approach.https://www.mdpi.com/1996-1073/13/4/1009dissolved gas analysisfuzzy logichealth indexpower transformersupport vector machine |
| spellingShingle | Rahman Azis Prasojo Harry Gumilang Suwarno Nur Ulfa Maulidevi Bambang Anggoro Soedjarno A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation Energies dissolved gas analysis fuzzy logic health index power transformer support vector machine |
| title | A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation |
| title_full | A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation |
| title_fullStr | A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation |
| title_full_unstemmed | A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation |
| title_short | A Fuzzy Logic Model for Power Transformer Faults’ Severity Determination Based on Gas Level, Gas Rate, and Dissolved Gas Analysis Interpretation |
| title_sort | fuzzy logic model for power transformer faults severity determination based on gas level gas rate and dissolved gas analysis interpretation |
| topic | dissolved gas analysis fuzzy logic health index power transformer support vector machine |
| url | https://www.mdpi.com/1996-1073/13/4/1009 |
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