Cyber attack protection and control in microgrids using channel code and semidefinite programming

Rana, MM; Li, L; Su, SW

Cyber attack protection and control in microgrids using channel code and semidefinite programming

Rana, MM

Li, L

Su, SW

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Publication Type:: Conference Proceeding
Citation:: IEEE Power and Energy Society General Meeting, 2016, 2016-November
Issue Date:: 2016-11-10

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Field	Value	Language
dc.contributor.author	Rana, MM https://orcid.org/0000-0003-2317-6327	en_US
dc.contributor.author	Li, L https://orcid.org/0000-0001-8485-2216	en_US
dc.contributor.author	Su, SW https://orcid.org/0000-0002-5720-8852	en_US
dc.date.available	2016-02-20	en_US
dc.date.issued	2016-11-10	en_US
dc.identifier.citation	IEEE Power and Energy Society General Meeting, 2016, 2016-November	en_US
dc.identifier.isbn	9781509041688	en_US
dc.identifier.issn	1944-9925	en_US
dc.identifier.uri	http://hdl.handle.net/10453/96769
dc.description.abstract	© 2016 IEEE. The smart grid has been considered as a nextgeneration power system to modernize the traditional grid to improve its security, connectivity and sustainability. Unfortunately, the grid is susceptible to malicious cyber attacks, which can create serious technical, economical and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional (RSC) code and Kalman filter based method in the context of microgrids. Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a posterior is used to recover the state information which is affected by random noises and cyber attacks. Once the estimated states are obtained, a semidefinite programming based optimal feedback controller is proposed to regulate the system states. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.	en_US
dc.relation.ispartof	IEEE Power and Energy Society General Meeting	en_US
dc.relation.isbasedon	10.1109/PESGM.2016.7741181	en_US
dc.title	Cyber attack protection and control in microgrids using channel code and semidefinite programming	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2016-November	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 Biomedical Engineering
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 - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2016-November	en_US

Abstract:

© 2016 IEEE. The smart grid has been considered as a nextgeneration power system to modernize the traditional grid to improve its security, connectivity and sustainability. Unfortunately, the grid is susceptible to malicious cyber attacks, which can create serious technical, economical and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional (RSC) code and Kalman filter based method in the context of microgrids. Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a posterior is used to recover the state information which is affected by random noises and cyber attacks. Once the estimated states are obtained, a semidefinite programming based optimal feedback controller is proposed to regulate the system states. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.

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http://hdl.handle.net/10453/96769