Model predictive power control of a brushless doubly fed twin stator induction generator

Wei, X; Cheng, M; Hua, W; Zhu, J; Yang, H

Model predictive power control of a brushless doubly fed twin stator induction generator

Wei, X Cheng, M Hua, W Zhu, J

Yang, H

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Publication Type:: Conference Proceeding
Citation:: 2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017, 2017, 2017-January pp. 5080 - 5085
Issue Date:: 2017-11-03

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Field	Value	Language
dc.contributor.author	Wei, X	en_US
dc.contributor.author	Cheng, M	en_US
dc.contributor.author	Hua, W	en_US
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Yang, H https://orcid.org/0000-0002-4987-5794	en_US
dc.date.issued	2017-11-03	en_US
dc.identifier.citation	2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017, 2017, 2017-January pp. 5080 - 5085	en_US
dc.identifier.isbn	9781509029983	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125817
dc.description.abstract	© 2017 IEEE. This paper presents a model predictive power control (MPPC) scheme for the brushless doubly fed twin stator induction generator (BDFTSIG). State-space equations of the BDFTSIG, in terms of power winding (PW) current, control winding (CW) current, and PW flux, is specifically derived. A complete power model, which clearly reveals the relationship between power and the applied voltage vector, is then developed for the first time to accurately predict the future behavior of power. The proposed MPPC is realized by optimizing a predefined objective function that represents the absolute power error. It takes into account the discrete nature of power converters and does not require any additional modulator. Digital simulations are implemented, which clearly indicate the effectiveness of the proposed MPPC in terms of both steady-state and dynamic performance.	en_US
dc.relation.ispartof	2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017	en_US
dc.relation.isbasedon	10.1109/ECCE.2017.8096856	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Model predictive power control of a brushless doubly fed twin stator induction generator	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-January	en_US
utslib.for	0906 Electrical and Electronic 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
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-January	en_US

Abstract:

© 2017 IEEE. This paper presents a model predictive power control (MPPC) scheme for the brushless doubly fed twin stator induction generator (BDFTSIG). State-space equations of the BDFTSIG, in terms of power winding (PW) current, control winding (CW) current, and PW flux, is specifically derived. A complete power model, which clearly reveals the relationship between power and the applied voltage vector, is then developed for the first time to accurately predict the future behavior of power. The proposed MPPC is realized by optimizing a predefined objective function that represents the absolute power error. It takes into account the discrete nature of power converters and does not require any additional modulator. Digital simulations are implemented, which clearly indicate the effectiveness of the proposed MPPC in terms of both steady-state and dynamic performance.

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http://hdl.handle.net/10453/125817