A Novel Fast Coupled Algorithm for Analyzing the Dynamic Behavior of the Bubble in the Transformer Oil Under the Electric Field
The presence of bubbles in the oil passage of the power transformer is extremely prone to cause partial discharges, which seriously jeopardizes the insulation strength. Therefore, it is crucial to study the dynamic characteristics of the bubble under the electric field and the bubble-induced electric field distortion before the oil passage is punctured. In this article, a coupled extended finite-element method-finite-volume method (XFEM-FVM) algorithm is proposed. The algorithm is used to improve the computational efficiency of the coupled electric-fluid field. XFEM is introduced to solve the Poisson equation for the electric field. The solved electric force will be used as source terms in the Navier-Stokes equation for the fluid field. The fluid field is solved by FVM. The level-set (LS) function transfers the bubble position between the two physical fields. It realizes the two fields coupled. Compared with the conventional method, the coupled algorithm only needs to dissect the mesh once in the whole time domain. The computational burden is reduced; meanwhile, the computational accuracy of both physical fields is ensured. The validity of the algorithm is finally verified by numerical simulations and experiments in two typical oil passages.
Authors
- Nana Duan (ORCID: https://orcid.org/0000-0002-4918-4651)
- Yulu Fan (ORCID: https://orcid.org/0000-0002-3467-9141)
- Xinyu Ma (ORCID: https://orcid.org/0000-0001-5353-0652)
- Yanxin Ren (ORCID: https://orcid.org/0009-0005-7963-6304)
- Weijie Xu (ORCID: https://orcid.org/0009-0009-3937-9664)
- Shuhong Wang (ORCID: https://orcid.org/0000-0002-5251-8704)
Institutions
- China XD Group (China) (CN)
- State Key Laboratory of Electrical Insulation and Power Equipment
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Dielectrics and Electrical Insulation
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1109/tdei.2024.3453786
- Citations
- 1
- Primary Topic
- Power Transformer Diagnostics and Insulation
- Type
- article
- Field-Weighted Citation Impact
- 0.21
Funders
- National Natural Science Foundation of China