Power transformers are the essential components in almost every electric power network. Uninterrupted operation of power transformers plays a critical role in guaranteeing the reliability and safety of the power grid. In this paper, aiming at predicting the reliability of large power transformers, multi-physics modeling and simulations are carried out based on three-dimensional (3D) finite element analysis (FEA) and finite volume method (FVM). Specifically, FEA electromagnetic modeling and simulation is performed in Ansys Maxwell to extract the transformer winding losses. Afterwards, thermal model is established in Ansys Fluent to obtain the temperature distribution, and more importantly to identify the transformer winding hot-spot temperature (HST). Accordingly, aging acceleration factor is determined by the winding HST. A sensitivity analysis is also conducted to determine the effects of oil properties on the temperature distribution and HST.
|Title of host publication||2022 IEEE Industry Applications Society Annual Meeting, IAS 2022|
|State||Published - 2022|
|Event||2022 IEEE Industry Applications Society Annual Meeting, IAS 2022 - Detroit, United States|
Duration: Oct 9 2022 → Oct 14 2022
|Name||Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)|
|Conference||2022 IEEE Industry Applications Society Annual Meeting, IAS 2022|
|Period||10/9/22 → 10/14/22|
Bibliographical noteFunding Information:
The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0001391. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
© 2022 IEEE.
- finite element analysis (FEA)
- finite volume method (FVM)
- hot-spot temperature
- Oil-immersed power transformer
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering