Open AccessThermal optimization research of oil-immersed transformer winding based on the support machine response surface
Author(s) -
Fan Yuan,
Wentao Yang,
Bo Tang,
Yue Wang,
Fa Guang Jiang,
Yilin Han,
Li Huang,
Can Ding
Publication year - 2022
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci210530264y
Subject(s) - particle swarm optimization , response surface methodology , transformer , support vector machine , computer science , thermal , optimal design , electromagnetic coil , winding machine , voltage , algorithm , mechanical engineering , physics , engineering , electrical engineering , artificial intelligence , machine learning , meteorology
In this paper, the CFD (computational fluid dynamics) model is established for the low voltage winding region of an oil-immersed transformer according to the design parameters, and the detailed temperature distribution within the region is obtained by numerical simulation. On this basis, the RSM (response surface methodology) is adopted to optimize the structure parameters with the purpose of minimizing the hot spot temperature. After a sequence of designed experiments, the second-order polynomial response surface and the SVM (support vector machine) response surface are established respectively. The analysis of their errors shows that the SVM response surface can be better used to fit the approximation. Finally, the PSO (particle swarm optimization) algorithm is employed to get the optimal structure parameters of the winding based on the SVM response surface. The results show that the optimization method can significantly reduce the hot spot temperature of the winding, which provides a guiding direction for the optimal design of the winding structure of transformers.