Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis
Existing interturn fault detecting methods rely on winding impedance, winding current, and dissolved gases. They are effective only when the insulation is severely damaged. This paper proposes a novel detection method based on fusion analysis of electrothermal characteristics including winding curre...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/179814 |
| _version_ | 1811678097957715968 |
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| author | Zhang, Lijing Sheng, Gehao Zhou, Nan Ni, Zizhan Jiang, Xiuchen |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Zhang, Lijing Sheng, Gehao Zhou, Nan Ni, Zizhan Jiang, Xiuchen |
| author_sort | Zhang, Lijing |
| collection | NTU |
| description | Existing interturn fault detecting methods rely on winding impedance, winding current, and dissolved gases. They are effective only when the insulation is severely damaged. This paper proposes a novel detection method based on fusion analysis of electrothermal characteristics including winding currents, temperatures of four areas on the tank wall, top oil and ambient temperatures, which can identify the interturn fault at an early stage. When an incipient interturn fault occurs, the heat generated by the faulty turns is transferred to the oil and tank wall, leading to an increase in top oil and tank wall temperatures. Thus, the incipient fault can be detected by analysing these electrothermal characteristic parameters. Borrowing the idea of digital twin (DT), this method establishes a high-fidelity simulation model to simulate the transformer electrothermal characteristics under different operating conditions. Afterward, an intelligent neural network is adopted to extract the quantitative relationship between the eight feature attributions and fault conditions. Finally, this neural network is utilized to detect the incipient interturn fault for the transformer entity. Case studies are conducted on a 100 kVA transformer with oil natural air natural (ONAN) cooling mode. The detection accuracy is improved by 68.5% compared to the winding current-based method. |
| first_indexed | 2024-10-01T02:47:51Z |
| format | Journal Article |
| id | ntu-10356/179814 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:47:51Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1798142024-08-30T15:40:18Z Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis Zhang, Lijing Sheng, Gehao Zhou, Nan Ni, Zizhan Jiang, Xiuchen School of Electrical and Electronic Engineering Engineering Fault diagnosis Power transformers Existing interturn fault detecting methods rely on winding impedance, winding current, and dissolved gases. They are effective only when the insulation is severely damaged. This paper proposes a novel detection method based on fusion analysis of electrothermal characteristics including winding currents, temperatures of four areas on the tank wall, top oil and ambient temperatures, which can identify the interturn fault at an early stage. When an incipient interturn fault occurs, the heat generated by the faulty turns is transferred to the oil and tank wall, leading to an increase in top oil and tank wall temperatures. Thus, the incipient fault can be detected by analysing these electrothermal characteristic parameters. Borrowing the idea of digital twin (DT), this method establishes a high-fidelity simulation model to simulate the transformer electrothermal characteristics under different operating conditions. Afterward, an intelligent neural network is adopted to extract the quantitative relationship between the eight feature attributions and fault conditions. Finally, this neural network is utilized to detect the incipient interturn fault for the transformer entity. Case studies are conducted on a 100 kVA transformer with oil natural air natural (ONAN) cooling mode. The detection accuracy is improved by 68.5% compared to the winding current-based method. Published version This work was supported in part by National Key Research and Development Program (2020YFB1709701). 2024-08-26T06:19:25Z 2024-08-26T06:19:25Z 2024 Journal Article Zhang, L., Sheng, G., Zhou, N., Ni, Z. & Jiang, X. (2024). Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis. IET Generation, Transmission and Distribution, 18(9), 1871-1884. https://dx.doi.org/10.1049/gtd2.13166 1751-8687 https://hdl.handle.net/10356/179814 10.1049/gtd2.13166 2-s2.0-85192106717 9 18 1871 1884 en IET Generation, Transmission and Distribution © 2024 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. application/pdf |
| spellingShingle | Engineering Fault diagnosis Power transformers Zhang, Lijing Sheng, Gehao Zhou, Nan Ni, Zizhan Jiang, Xiuchen Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title | Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title_full | Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title_fullStr | Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title_full_unstemmed | Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title_short | Incipient interturn fault detection for ONAN power transformers using electrothermal characteristic fusion analysis |
| title_sort | incipient interturn fault detection for onan power transformers using electrothermal characteristic fusion analysis |
| topic | Engineering Fault diagnosis Power transformers |
| url | https://hdl.handle.net/10356/179814 |
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