Multilevel Robust Design Optimization of a Superconducting Magnetic Energy Storage Based on a Benchmark Study

Lei, G; Liu, C; Jafari, M; Zhu, J; Guo, Y

Multilevel Robust Design Optimization of a Superconducting Magnetic Energy Storage Based on a Benchmark Study

Lei, G

Liu, C Jafari, M

Zhu, J

Guo, Y

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Applied Superconductivity, 2016, 26 (7)
Issue Date:: 2016-10-01

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Field	Value	Language
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802	en_US
dc.contributor.author	Liu, C	en_US
dc.contributor.author	Jafari, M https://orcid.org/0000-0002-8521-8636	en_US
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684	en_US
dc.date.issued	2016-10-01	en_US
dc.identifier.citation	IEEE Transactions on Applied Superconductivity, 2016, 26 (7)	en_US
dc.identifier.issn	1051-8223	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122989
dc.description.abstract	© 2016 IEEE. Superconducting magnetic energy storage (SMES) systems with different superconducting materials are attracting great attentions and funding from the governments around the world because they are promising large-scale energy storage devices for future smart grid. Due to the high cost of SMES, its manufacturing quality and operation reliability have to be investigated in the design optimization stage. This paper presents a robust design optimization method to solve this issue based on a benchmark problem, TEAM problem 22. The proposed method is based on a technique called design for Six Sigma. Meanwhile, a three-level optimization framework is employed to reduce the computation cost of a finite-element analysis due to high-dimensional design space and Monte-Carlo analysis. As shown, the manufacturing reliability and quality of the investigated SMES after robust optimization have been increased greatly.	en_US
dc.relation.ispartof	IEEE Transactions on Applied Superconductivity	en_US
dc.relation.isbasedon	10.1109/TASC.2016.2599703	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	General Physics	en_US
dc.title	Multilevel Robust Design Optimization of a Superconducting Magnetic Energy Storage Based on a Benchmark Study	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	26	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0204 Condensed Matter Physics	en_US
utslib.for	0912 Materials Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
utslib.copyright.status	open_access	*
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	26	en_US

Abstract:

© 2016 IEEE. Superconducting magnetic energy storage (SMES) systems with different superconducting materials are attracting great attentions and funding from the governments around the world because they are promising large-scale energy storage devices for future smart grid. Due to the high cost of SMES, its manufacturing quality and operation reliability have to be investigated in the design optimization stage. This paper presents a robust design optimization method to solve this issue based on a benchmark problem, TEAM problem 22. The proposed method is based on a technique called design for Six Sigma. Meanwhile, a three-level optimization framework is employed to reduce the computation cost of a finite-element analysis due to high-dimensional design space and Monte-Carlo analysis. As shown, the manufacturing reliability and quality of the investigated SMES after robust optimization have been increased greatly.

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http://hdl.handle.net/10453/122989