Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning
This paper explores the design parameters of high-voltage coils of three-phase transformers and the effects of eddy current losses caused by energy conversion. The commercial software, ANSYS-Maxwell, was employed to conduct the simulation of electrical and magnetic fields. The design parameters of t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-02-01
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| Series: | Energy Reports |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484719310376 |
| _version_ | 1819011624235696128 |
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| author | Han-Chieh Chiu Hung-Kang Pao Ren-Hong Hsieh Yu-Jen Chiu Jer-Huan Jang |
| author_facet | Han-Chieh Chiu Hung-Kang Pao Ren-Hong Hsieh Yu-Jen Chiu Jer-Huan Jang |
| author_sort | Han-Chieh Chiu |
| collection | DOAJ |
| description | This paper explores the design parameters of high-voltage coils of three-phase transformers and the effects of eddy current losses caused by energy conversion. The commercial software, ANSYS-Maxwell, was employed to conduct the simulation of electrical and magnetic fields. The design parameters of the high voltage coil include the leg distance of core, the height and the block thickness of primary windings, the height of primary coils, and the height of secondary windings. The specification of the three-phase transformer of this study are 3000 kVA with rated voltage of 6600 V and corresponding current of 151.5 A. Base on thirty cases of simulation, machine learning, artificial neural network, was utilized to predict the extra loss due to eddy current in the clamps and the windings. The prediction accuracies are 0.72 and 0.86 for primary and secondary windings, respectively. Keywords: Dry-type transformer, Eddy current loss, Numerical simulation, Machine learning |
| first_indexed | 2024-12-21T01:31:07Z |
| format | Article |
| id | doaj.art-00623b1dc52e4f5a9456335497ad0e24 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-12-21T01:31:07Z |
| publishDate | 2020-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-00623b1dc52e4f5a9456335497ad0e242022-12-21T19:20:21ZengElsevierEnergy Reports2352-48472020-02-016447451Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learningHan-Chieh Chiu0Hung-Kang Pao1Ren-Hong Hsieh2Yu-Jen Chiu3Jer-Huan Jang4Department of Mechanical Engineering, Taipei City University of Science and Technology, Taipei 112, TaiwanSwitchgear Unit Engineering Division, Nanya Plastic Corporation, Taipei 105, TaiwanDepartment of Mechanical Engineering, Taipei City University of Science and Technology, Taipei 112, TaiwanDepartment of Mechanical Engineering, Taipei City University of Science and Technology, Taipei 112, TaiwanDepartment of Mechanical Engineering/Battery Center of Green Energy, Ming Chi University of Technology, New Taipei City 243, Taiwan; Corresponding author.This paper explores the design parameters of high-voltage coils of three-phase transformers and the effects of eddy current losses caused by energy conversion. The commercial software, ANSYS-Maxwell, was employed to conduct the simulation of electrical and magnetic fields. The design parameters of the high voltage coil include the leg distance of core, the height and the block thickness of primary windings, the height of primary coils, and the height of secondary windings. The specification of the three-phase transformer of this study are 3000 kVA with rated voltage of 6600 V and corresponding current of 151.5 A. Base on thirty cases of simulation, machine learning, artificial neural network, was utilized to predict the extra loss due to eddy current in the clamps and the windings. The prediction accuracies are 0.72 and 0.86 for primary and secondary windings, respectively. Keywords: Dry-type transformer, Eddy current loss, Numerical simulation, Machine learninghttp://www.sciencedirect.com/science/article/pii/S2352484719310376 |
| spellingShingle | Han-Chieh Chiu Hung-Kang Pao Ren-Hong Hsieh Yu-Jen Chiu Jer-Huan Jang Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning Energy Reports |
| title | Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning |
| title_full | Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning |
| title_fullStr | Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning |
| title_full_unstemmed | Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning |
| title_short | Estimation of the eddy current losses in a dry-type 3000 KVA transformer with machine learning |
| title_sort | estimation of the eddy current losses in a dry type 3000 kva transformer with machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2352484719310376 |
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