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Interaction analysis and multi-response optimization of transformer winding design parameters

Citation

Tan, Y and Yu, X and Wang, X and Lv, Q and Shi, M, Interaction analysis and multi-response optimization of transformer winding design parameters, International Communications in Heat and Mass Transfer, 137 Article 106233. ISSN 0735-1933 (2022) [Refereed Article]


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DOI: doi:10.1016/j.icheatmasstransfer.2022.106233

Abstract

This work conducted a multi-response optimization on the design parameter of a transformer winding based on the response surface methodology and desirability function approach to find a design with better combined-thermal-hydraulic performance. A numerical experiment was performed with two-dimensional axisymmetric numerical heat transfer models. Response surface models were established based on experimental results and checked through analyses of variance. Regression equations were fitted and then verified. Interactions among factors were investigated in detail. A multi-response optimization was carried out on the winding design parameters and optimum design was identified using the desirability function approach. The results showed that the response surface models built up in this work were all significant and all the responses could be predicted accurately based on the regression equations. The design with the block washer number of 1, axial duct size of 8 mm and radial duct size of 3 mm was found as the optimum winding design of this work. Compared with the conventional design, the optimum design increased the Colburn-j factor and Darcy friction factor by 212% and 9%, respectively, simultaneously decreased the maximum and mean temperature rises by 67.1% and 70.5%, respectively.

Item Details

Item Type:Refereed Article
Keywords:transformer winding; Interaction, multi-response optimization, response surface methodology, desirability function approach
Research Division:Engineering
Research Group:Mechanical engineering
Research Field:Energy generation, conversion and storage (excl. chemical and electrical)
Objective Division:Energy
Objective Group:Energy storage, distribution and supply
Objective Field:Energy systems and analysis
UTAS Author:Wang, X (Professor Xiaolin Wang)
ID Code:151095
Year Published:2022
Deposited By:Engineering
Deposited On:2022-07-18
Last Modified:2022-07-26
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