Open AccessOptimisation design of medium frequency transformer for the offshore dc grid based on multi‐objective genetic algorithm
Author(s) -
Zhang Liang,
Zhang Dan,
Shui Henghua,
Yuan Yubo,
Pei Qian,
Zhu Jihong
Publication year - 2017
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2017.0309
Subject(s) - transformer , genetic algorithm , grid , computer science , submarine pipeline , algorithm , electrical engineering , engineering , mathematics , voltage , machine learning , geometry , geotechnical engineering
A DC/DC converter is a vital component for offshore DC grids, in which a medium frequency transformer (MFT) is the main element. Therefore, it is necessary to optimise the core material and the design method so that the loss of the MFT would be reduced. In this study, the multi‐objective genetic algorithm is proposed, by which two MFTs with different core materials are both optimised. The magnetic flux density of the transformer core and the current density of the windings are introduced as the optimised variables. Also, the key equations for transformer design are put forward as the objective functions. Moreover, with constant iteration of the process of segmentation, parallel selection, mergence, recombination and variation, the Pareto optimal solution is determined. Furthermore, to verify the optimisation results, the temperature field and electric strength of the amorphous alloy MFT are calculated and simulated by finite‐element analysis. Finally, a MFT prototype with an amorphous alloy core is built, and the experiment is carried out.