Multiscale electromagnetic–thermal–fluid field coupling model for oil-immersed transformers
Accurate predictions of the hotspot temperatures within large oil-immersed transformers are critical to their operational safety and longevity. The present work explores a novel multiscale electromagnetic–thermal–fluid indirect coupling model to address this challenge. The novelty of the model lies in its comprehensive integration of a detailed disc-type winding structure with the complete radiator-cooling circuit to overcome the common simplifications applied in existing studies. The proposed methodology involves a sequential process, where a 3D electromagnetic field simulation is first performed to determine the loss distribution precisely; here, the total eddy current loss of the winding accounts for 3.68% of the total winding loss and shows a U-shaped distribution in the winding disc height direction. These losses are then imported as heat sources into a full-scale thermal–fluid model. The key findings of the model are that the eddy current losses of the winding account for a significant portion of the total loss and that their distribution critically influences the temperature field; further, the presence of oil washers creates localized temperature differences of up to 5.3 K. The model accuracy is strongly validated through a transformer temperature rise test using embedded optical-fiber sensors, and the results show a maximum deviation of only 3.1 K. Hence, the present study provides a high-fidelity simulation framework for transformer thermal management and design optimization.
Authors
- Mingzhi Peng
- R. Jiao (ORCID: https://orcid.org/0009-0006-9385-7661)
- Yu Hao Wang (ORCID: https://orcid.org/0000-0003-3914-9358)
- Tiantian Liu (ORCID: https://orcid.org/0000-0002-2395-9527)
- Yao Xu (ORCID: https://orcid.org/0009-0006-4823-2187)
- Yongbo Hu
Institutions
- State Grid Corporation of China (China) (CN)
Publication Details
- Journal
- Frontiers in Mechanical Engineering
- Published
- 2025-11-24
- DOI
- https://doi.org/10.3389/fmech.2025.1701541
- Citations
- 1
- Primary Topic
- Power Transformer Diagnostics and Insulation
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- State Grid Corporation of China