An Optimized Distributed Cooperative Control to Improve the Charging Performance of Battery Energy Storage in a Multiphotovoltaic Islanded DC Microgrid

Poursafar, N; Taghizadeh, S; J. Hossain, M; M. Guerrero, J

An Optimized Distributed Cooperative Control to Improve the Charging Performance of Battery Energy Storage in a Multiphotovoltaic Islanded DC Microgrid

Poursafar, N Taghizadeh, S J. Hossain, M M. Guerrero, J

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Systems Journal, 2022, 16, (1), pp. 1170-1181
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Poursafar, N
dc.contributor.author	Taghizadeh, S
dc.contributor.author	J. Hossain, M
dc.contributor.author	M. Guerrero, J
dc.date.accessioned	2023-03-20T02:21:37Z
dc.date.available	2023-03-20T02:21:37Z
dc.date.issued	2022-01-01
dc.identifier.citation	IEEE Systems Journal, 2022, 16, (1), pp. 1170-1181
dc.identifier.issn	1932-8184
dc.identifier.issn	1937-9234
dc.identifier.uri	http://hdl.handle.net/10453/167698
dc.description.abstract	When multi-photovoltaic (PV) energy sources are installed in dc microgrids (DCMGs), an optimized distributed controller is essential to provide efficient, economical, and reliable operation. This article proposes an optimized distributed cooperative control method for multi-PV energy sources in an islanded DCMG. Unlike conventional control methods for DCMGs, the proposed distributed cooperative control method is capable of obtaining a constant total generated power from PVs, thus minimizing the impact of the intermittent nature of PVs on the total generation. This operation subsequently reduces the charging stress on the backup energy storage system (BESS) and increases the lifetime of the BESS in the DCMG. The proposed control method can also intelligently reduce the total generation cost of the DCMG via monitoring and analyzing the information of energy sources and minimizing the quadratic cost function. The dynamic model of the proposed controller is thoroughly analyzed, and its effectiveness in terms of providing controllable generated power and cost reduction is validated for different generation-demand scenarios.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Systems Journal
dc.relation.isbasedon	10.1109/JSYST.2021.3070883
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Operations Research
dc.title	An Optimized Distributed Cooperative Control to Improve the Charging Performance of Battery Energy Storage in a Multiphotovoltaic Islanded DC Microgrid
dc.type	Journal Article
utslib.citation.volume	16
utslib.for	0906 Electrical and Electronic Engineering
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
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-03-20T02:21:36Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	16
utslib.citation.issue	1

Abstract:

When multi-photovoltaic (PV) energy sources are installed in dc microgrids (DCMGs), an optimized distributed controller is essential to provide efficient, economical, and reliable operation. This article proposes an optimized distributed cooperative control method for multi-PV energy sources in an islanded DCMG. Unlike conventional control methods for DCMGs, the proposed distributed cooperative control method is capable of obtaining a constant total generated power from PVs, thus minimizing the impact of the intermittent nature of PVs on the total generation. This operation subsequently reduces the charging stress on the backup energy storage system (BESS) and increases the lifetime of the BESS in the DCMG. The proposed control method can also intelligently reduce the total generation cost of the DCMG via monitoring and analyzing the information of energy sources and minimizing the quadratic cost function. The dynamic model of the proposed controller is thoroughly analyzed, and its effectiveness in terms of providing controllable generated power and cost reduction is validated for different generation-demand scenarios.

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http://hdl.handle.net/10453/167698