Battery Energy Storage Capacity Estimation for Microgrids Using Digital Twin Concept

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aut.relation.articlenumber4540
aut.relation.endpage4540
aut.relation.issue12
aut.relation.journalEnergies
aut.relation.startpage4540
aut.relation.volume16
dc.contributor.authorPadmawansa, Nisitha
dc.contributor.authorGunawardane, Kosala
dc.contributor.authorMadanian, Samaneh
dc.contributor.authorThan Oo, Amanullah Maung
dc.date.accessioned2023-06-12T01:04:38Z
dc.date.available2023-06-12T01:04:38Z
dc.date.issued2023-06-06
dc.description.abstractGlobally, 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.identifier.citationEnergies, ISSN: 1996-1073 (Print); 1996-1073 (Online), MDPI AG, 16(12), 4540-4540. doi: 10.3390/en16124540
dc.identifier.doi10.3390/en16124540
dc.identifier.issn1996-1073
dc.identifier.issn1996-1073
dc.identifier.urihttps://hdl.handle.net/10292/16244
dc.languageen
dc.publisherMDPI AG
dc.relation.urihttps://www.mdpi.com/1996-1073/16/12/4540
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject40 Engineering
dc.subject4008 Electrical Engineering
dc.subject4009 Electronics, Sensors and Digital Hardware
dc.subject7 Affordable and Clean Energy
dc.subject13 Climate Action
dc.subject02 Physical Sciences
dc.subject09 Engineering
dc.subject33 Built environment and design
dc.subject40 Engineering
dc.subject51 Physical sciences
dc.titleBattery Energy Storage Capacity Estimation for Microgrids Using Digital Twin Concept
dc.typeJournal Article
pubs.elements-id508988
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