Multi‐Objective Optimization Design of Linear Phase Shift Transformer Based on Improved Differential Evolutionary Algorithm

Linear phase shifting transformer is a new type of phase shifting transformer with the advantages of simple winding structure, easy modularity, and the ability to shift phase at any angle. In order to improve the efficiency and power factor of linear phase shift transformer and reduce the weight of...

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Bibliographic Details
Published in:IEEJ transactions on electrical and electronic engineering Vol. 18; no. 9; pp. 1439 - 1450
Main Authors: Zhou, Changduo, Zhao, Jinghong, Wang, Hanming, Yan, Sinian, Yan, Dongao
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.09.2023
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ISSN:1931-4973, 1931-4981
Online Access:Get full text
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Summary:Linear phase shifting transformer is a new type of phase shifting transformer with the advantages of simple winding structure, easy modularity, and the ability to shift phase at any angle. In order to improve the efficiency and power factor of linear phase shift transformer and reduce the weight of the body, based on the equivalent circuit, this paper first, selects the main design parameters of the linear phase shift transformer model as the optimization object, secondly, selects the constraints and objective function applicable to this model, and then, establishes the linear phase shift transformer optimization design model. Finally, a differential evolutionary algorithm with strong global search performance is used to optimize the design parameters. Taking the 1 kW linear phase shifting transformer as an example, the efficiency, power factor, and weight before and after optimization are compared using finite element simulation to verify the effectiveness of the proposed optimization method. The test results of the experimental prototype prove that the proposed method can effectively solve the optimization design problem of linear phase shifting transformers. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
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ISSN:1931-4973
1931-4981
DOI:10.1002/tee.23877