Battery Energy Storage Capacity Estimation for Microgrids Using Digital Twin Concept

Padmawansa, N; Gunawardane, K; Madanian, S; Than Oo, AM

Battery Energy Storage Capacity Estimation for Microgrids Using Digital Twin Concept

Padmawansa, N Gunawardane, K Madanian, S Than Oo, AM

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Energies, 2023, 16, (12)
Issue Date:: 2023-06-01

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Field	Value	Language
dc.contributor.author	Padmawansa, N
dc.contributor.author	Gunawardane, K
dc.contributor.author	Madanian, S
dc.contributor.author	Than Oo, AM
dc.date.accessioned	2024-01-16T04:55:48Z
dc.date.available	2024-01-16T04:55:48Z
dc.date.issued	2023-06-01
dc.identifier.citation	Energies, 2023, 16, (12)
dc.identifier.issn	1996-1073
dc.identifier.issn	1996-1073
dc.identifier.uri	http://hdl.handle.net/10453/174588
dc.description.abstract	Globally, renewable energy-based power generation is experiencing exponential growth due to concerns over the environmental impacts of traditional power generation methods. Microgrids (MGs) are commonly employed to integrate renewable sources due to their distributed nature, with batteries often used to compensate for power fluctuations caused by the intermittency of renewable energy sources. However, sudden fluctuations in the power supply can negatively impact battery performance, making it challenging to select an appropriate battery energy storage system (BESS) at the design stage of an MG. The cycle count of a battery in relation to battery stress is a useful measure for determining the general health of a battery and can aid in BESS selection. An accurate digital replica of an MG is required to determine the required cycle count and stress levels of a BESS. The Digital Twin (DT) concept can be used to replicate the dynamics of the MG in a virtual environment, allowing for the estimation of required cycle numbers and applied stress levels to a BESS. This paper presents a Microgrid Digital Twin (MGDT) model that can estimate the required cycle count and stress levels of a BESS without considering any unique battery type. Based on the results, designers can select an appropriate BESS for the MG, and the MGDT can also be used to roughly estimate the health of the currently operating BESS, allowing for cost-effective predictive maintenance scheduling for MGs.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Energies
dc.relation.isbasedon	10.3390/en16124540
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	02 Physical Sciences, 09 Engineering
dc.subject.classification	33 Built environment and design
dc.subject.classification	40 Engineering
dc.subject.classification	51 Physical sciences
dc.title	Battery Energy Storage Capacity Estimation for Microgrids Using Digital Twin Concept
dc.type	Journal Article
utslib.citation.volume	16
utslib.for	02 Physical Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-16T04:55:47Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	16
utslib.citation.issue	12

Abstract:

Globally, renewable energy-based power generation is experiencing exponential growth due to concerns over the environmental impacts of traditional power generation methods. Microgrids (MGs) are commonly employed to integrate renewable sources due to their distributed nature, with batteries often used to compensate for power fluctuations caused by the intermittency of renewable energy sources. However, sudden fluctuations in the power supply can negatively impact battery performance, making it challenging to select an appropriate battery energy storage system (BESS) at the design stage of an MG. The cycle count of a battery in relation to battery stress is a useful measure for determining the general health of a battery and can aid in BESS selection. An accurate digital replica of an MG is required to determine the required cycle count and stress levels of a BESS. The Digital Twin (DT) concept can be used to replicate the dynamics of the MG in a virtual environment, allowing for the estimation of required cycle numbers and applied stress levels to a BESS. This paper presents a Microgrid Digital Twin (MGDT) model that can estimate the required cycle count and stress levels of a BESS without considering any unique battery type. Based on the results, designers can select an appropriate BESS for the MG, and the MGDT can also be used to roughly estimate the health of the currently operating BESS, allowing for cost-effective predictive maintenance scheduling for MGs.

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http://hdl.handle.net/10453/174588