Finite-Set Model Predictive Power Control of Brushless Doubly Fed Twin Stator Induction Generator

Wei, X; Cheng, M; Zhu, J; Yang, H; Luo, R

Finite-Set Model Predictive Power Control of Brushless Doubly Fed Twin Stator Induction Generator

Wei, X Cheng, M Zhu, J

Yang, H

Luo, R

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Power Electronics, 2019, 34 (3), pp. 2300 - 2311
Issue Date:: 2019-03-01

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Field	Value	Language
dc.contributor.author	Wei, X	en_US
dc.contributor.author	Cheng, M	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.contributor.author	Luo, R	en_US
dc.date.issued	2019-03-01	en_US
dc.identifier.citation	IEEE Transactions on Power Electronics, 2019, 34 (3), pp. 2300 - 2311	en_US
dc.identifier.issn	0885-8993	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131899
dc.description.abstract	© 1986-2012 IEEE. This paper presents a finite-set model predictive power control (FS-MPPC) method for the brushless doubly fed twin stator induction generator (BDFTSIG) in variable speed constant frequency generation applications. The FS-MPPC controller is developed in a general reference frame from which all other reference frames can be deduced readily. The invariant feature of the predictive power model in various reference frames contributes to the reference frame-free characteristic of the developed FS-MPPC controller, enabling its application more flexible and universal. Besides, the arduous process of control winding flux estimation is avoided in the FS-MPPC controller by choosing state variables that are easy to be obtained. Moreover, the influence of rotor circuit that has long been neglected in the existing controllers for the brushless doubly fed induction machines is embedded within the predictive power model and inherently considered in the FS-MPPC controller, which contributes to accurate power control of the BDFTSIG. Furthermore, the feasibility and effectiveness of the developed FS-MPPC controller regarding different power levels and grid fault conditions are briefly discussed. Finally, numerical simulations and experimental tests are carried out, which demonstrates the effectiveness of the developed FS-MPPC controller.	en_US
dc.relation.ispartof	IEEE Transactions on Power Electronics	en_US
dc.relation.isbasedon	10.1109/TPEL.2018.2845129	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Electrical & Electronic Engineering	en_US
dc.title	Finite-Set Model Predictive Power Control of Brushless Doubly Fed Twin Stator Induction Generator	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	34	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.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	34	en_US

Abstract:

© 1986-2012 IEEE. This paper presents a finite-set model predictive power control (FS-MPPC) method for the brushless doubly fed twin stator induction generator (BDFTSIG) in variable speed constant frequency generation applications. The FS-MPPC controller is developed in a general reference frame from which all other reference frames can be deduced readily. The invariant feature of the predictive power model in various reference frames contributes to the reference frame-free characteristic of the developed FS-MPPC controller, enabling its application more flexible and universal. Besides, the arduous process of control winding flux estimation is avoided in the FS-MPPC controller by choosing state variables that are easy to be obtained. Moreover, the influence of rotor circuit that has long been neglected in the existing controllers for the brushless doubly fed induction machines is embedded within the predictive power model and inherently considered in the FS-MPPC controller, which contributes to accurate power control of the BDFTSIG. Furthermore, the feasibility and effectiveness of the developed FS-MPPC controller regarding different power levels and grid fault conditions are briefly discussed. Finally, numerical simulations and experimental tests are carried out, which demonstrates the effectiveness of the developed FS-MPPC controller.

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http://hdl.handle.net/10453/131899