Deployment of electric buses: Planning the fleet size and type, charging infrastructure and operations with an optimization-based model

dc.contributor.authorGrilo T. C.
dc.contributor.authorKalakou, S.
dc.contributor.authorFernandes, J.
dc.contributor.editorMartins, A. L., Ferreira, J. C., Kocian, A., and Costa, V.
dc.date.accessioned2022-05-20T15:03:20Z
dc.date.available2022-05-20T15:03:20Z
dc.date.issued2020
dc.date.updated2022-05-20T16:02:41Z
dc.description.abstractThe current awareness about climate change creates the urgency in adjusting the services provided in public transport towards more sustainable operations. Recent studies have shown that the integration of electric vehicles into existing fleets is an alternative that allows reducing CO2 emissions, thus contributing to a more sustainable provision of services in the sector. When the aim is to achieve a full electrification of a bus fleet, several decisions need to be planned, such as i) the number of buses that are required, ii) the types of batteries used in those vehicles, iii) the charging technologies and strategies, iv) the location of the charging stations, and v) the frequency of charging. Nevertheless, although several planning studies have focused on the full electrification of a bus fleet, no study was found considering all these planning decisions that are deemed as essential for an adequate planning. Our study thus contributes to this gap in the literature, by proposing an optimization-based planning model that considers all these planning dimensions in the decision-making process related to the integration of electric buses in a public bus transport system – the MILP4ElectFleet model. All these decisions are evaluated while ensuring the minimization of in-vestment and operating costs. The MILP4ElectFleet model is applied to the Car-ris case study, a Portuguese public transport operator in the metropolitan area of Lisbon.eng
dc.description.versioninfo:eu-repo/semantics/acceptedVersion
dc.event.date2020
dc.event.locationPortoeng
dc.event.title4th EAI International Conference on Intelligent Transport Systems, INTSYS 2020
dc.event.typeConferênciapt
dc.identifier.doi10.1007/978-3-030-71454-3_11
dc.identifier.isbn978-3-030-71454-3
dc.identifier.issn1867-8211
dc.identifier.urihttp://hdl.handle.net/10071/25498
dc.journalIntelligent Transport Systems, From Research and Development to the Market Uptake. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
dc.language.isoeng
dc.pagination175 - 193
dc.peerreviewedyes
dc.publisherSpringer Cham
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00315%2F2020/PT
dc.rightsopen access
dc.subjectElectric bus fleeteng
dc.subjectPublic transporteng
dc.subjectOptimizationeng
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Civilpor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologiaspor
dc.titleDeployment of electric buses: Planning the fleet size and type, charging infrastructure and operations with an optimization-based modeleng
dc.typeconferenceObject
dc.volume364
degois.publication.firstPage175
degois.publication.lastPage193
degois.publication.locationPortoeng
degois.publication.titleDeployment of electric buses: Planning the fleet size and type, charging infrastructure and operations with an optimization-based modeleng
dspace.entity.typePublicationen
iscte.alternateIdentifiers.scopus2-s2.0-85104402188
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-78313
iscte.subject.odsEnergias renováveis e acessíveispor
iscte.subject.odsIndústria, inovação e infraestruturaspor
iscte.subject.odsCidades e comunidades sustentáveispor

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