A digital twin of charging stations for fleets of electric vehicles

Francisco, André; Monteiro, Jânio; Cardoso, Pedro

Publication

A digital twin of charging stations for fleets of electric vehicles

2023Journal article

dc.contributor.author	Francisco, André
dc.contributor.author	Monteiro, Jânio
dc.contributor.author	Cardoso, Pedro
dc.date.accessioned	2024-01-03T11:04:31Z
dc.date.available	2024-01-03T11:04:31Z
dc.date.issued	2023
dc.description.abstract	The increasing concern over the environmental impact of fossil fuels and associated CO2 emissions created a growing interest on the use of electric vehicles (EVs) and green energy utilization. In this context, the widespread adoption of EVs should be accompanied by the introduction of generation from renewable energy sources (RES). That insertion, at the distribution level, presents challenges that result from their intermittent nature, requiring demand-response measures that can be addressed by adjusting the charging processes to match the available power. In the framework of EVs renting companies, it is essential to have an efficient charging management that allows achieving high levels of self-consumption and self-sufficiency, lower operational costs and lower payback periods for the investments made. The utilization of digital twins (DTs) can be key to achieve those goals, providing accurate simulations and predictions. Their use in the context of EV charging can offer valuable insights into optimizing charging scheduling and predicting energy demands, taking into consideration distinct scenarios. This paper presents the work done to implement DTs of a set of charging stations (CSs) and EVs, which allow the modeling and improved management of the charging processes of EV fleets, for a set of CSs, integrating RES. In this charging context, experimental results using the DT were applied considering a predicted mobility. The applied scenarios supported an effective and optimized managing performance, reaching low paybacks and high self-sufficiency values. The obtained results show that this method is a viable and cost-effective solution for companies renting EVs.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.doi	10.1109/ACCESS.2023.3330833	pt_PT
dc.identifier.issn	2169-3536
dc.identifier.uri	http://hdl.handle.net/10400.1/20253
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE - Institute of Electrical and Electronics Engineers	pt_PT
dc.relation	Laboratory of Robotics and Engineering Systems
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	pt_PT
dc.subject	Digital twin	pt_PT
dc.subject	Electric vehicles	pt_PT
dc.subject	Fleets	pt_PT
dc.subject	Smart charging	pt_PT
dc.subject	Renewable energy sources	pt_PT
dc.title	A digital twin of charging stations for fleets of electric vehicles	pt_PT
dc.type	journal article
dspace.entity.type	Publication
oaire.awardTitle	Laboratory of Robotics and Engineering Systems
oaire.awardURI	info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50009%2F2020/PT
oaire.citation.endPage	125683	pt_PT
oaire.citation.startPage	125664	pt_PT
oaire.citation.title	IEEE Access	pt_PT
oaire.citation.volume	11	pt_PT
oaire.fundingStream	6817 - DCRRNI ID
person.familyName	Francisco
person.familyName	Monteiro
person.familyName	Cardoso
person.givenName	André
person.givenName	Jânio
person.givenName	Pedro
person.identifier	R-001-H74
person.identifier.ciencia-id	D01E-51A1-1B88
person.identifier.ciencia-id	D019-1CF7-B156
person.identifier.ciencia-id	5F10-1C37-FE45
person.identifier.orcid	0000-0003-0900-5417
person.identifier.orcid	0000-0002-4203-1679
person.identifier.orcid	0000-0003-4803-7964
person.identifier.rid	O-3416-2015
person.identifier.rid	G-6405-2013
person.identifier.scopus-author-id	35606413800
person.identifier.scopus-author-id	35602693500
project.funder.identifier	http://doi.org/10.13039/501100001871
project.funder.name	Fundação para a Ciência e a Tecnologia
rcaap.rights	openAccess	pt_PT
rcaap.type	article	pt_PT
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