Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99004
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorHuang, Den_US
dc.creatorWang, Sen_US
dc.date.accessioned2023-06-08T01:09:06Z-
dc.date.available2023-06-08T01:09:06Z-
dc.identifier.issn2772-5871en_US
dc.identifier.urihttp://hdl.handle.net/10397/99004-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2022 The Authors. Published by Elsevier Ltd on behalf of Southeast University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Huang, D., & Wang, S. (2022). A two-stage stochastic programming model of coordinated electric bus charging scheduling for a hybrid charging scheme. Multimodal Transportation, 1(1), 100006 is available at https://doi.org/10.1016/j.multra.2022.100006.en_US
dc.subjectElectric busen_US
dc.subjectCharging schedulingen_US
dc.subjectStochastic programmingen_US
dc.subjectPlug-in chargingen_US
dc.subjectBattery swappingen_US
dc.titleA two-stage stochastic programming model of coordinated electric bus charging scheduling for a hybrid charging schemeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume1en_US
dc.identifier.issue1en_US
dc.identifier.doi10.1016/j.multra.2022.100006en_US
dcterms.abstractThis paper proposes a coordinated charging scheduling approach for battery electric buses (BEBs) in a hybrid charging scheme, i.e., both plug-in fast charging and battery-swapping charging modes are incorporated in a single charging station. To accommodate the uncertain battery energy consumption during bus operation, a two-stage stochastic program is formulated, where the first stage decision determines the battery inventory level of each station and the second stage determines the charging mode and designs when, where, and how long each bus should be charged. Future uncertainties associated with energy consumption are captured by a set of possible discrete scenarios from historical data. A progressive hedging algorithm is developed to decompose the two-stage stochastic program into sub-problems. A case study is conducted to verify the proposed models and solution algorithms.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMultimodal transportation, Mar. 2022, v. 1, no. 1, 100006en_US
dcterms.isPartOfMultimodal transportationen_US
dcterms.issued2022-03-
dc.identifier.eissn2772-5863en_US
dc.identifier.artn100006en_US
dc.description.validate202306 bcwwen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2085-
dc.identifier.SubFormID46508-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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