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dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.creatorZhang, Len_US
dc.creatorWang, Yen_US
dc.creatorGu, Wen_US
dc.creatorHan, Yen_US
dc.creatorChung, Een_US
dc.creatorQu, Xen_US
dc.date.accessioned2023-12-11T03:21:05Z-
dc.date.available2023-12-11T03:21:05Z-
dc.identifier.issn1093-9687en_US
dc.identifier.urihttp://hdl.handle.net/10397/103520-
dc.language.isoenen_US
dc.publisherWiley-Blackwell Publishing, Inc.en_US
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.en_US
dc.rights© 2023 The Authors. Computer-Aided Civil and Infrastructure Engineering published by Wiley Periodicals LLC on behalf of Editor.en_US
dc.rightsThe following publication Zhang, L., Wang, Y., Gu, W., Han, Y., Chung, E., & Qu, X. (2023). On the role of time-of-use electricity price in charge scheduling for electric bus fleets. Computer-Aided Civil and Infrastructure Engineering, 39, 1218–1237 is available at https://doi.org/10.1111/mice.13134.en_US
dc.titleOn the role of time-of-use electricity price in charge scheduling for electric bus fleetsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1218en_US
dc.identifier.epage1237en_US
dc.identifier.volume39en_US
dc.identifier.issue8en_US
dc.identifier.doi10.1111/mice.13134en_US
dcterms.abstractAs electric buses become increasingly popular, it is imperative to optimize the schedules of electric buses with explicit consideration of their charging requirements. Unfortunately, existing studies failed to properly model the impacts of essential operating factors, including the time-of-use (TOU) electricity price, partial charging, and limited chargers. Our paper proposes a mixed-integer nonlinear program to minimize the total operating cost of an electric bus fleet for fulfilling a group of timetabled trips, considering the above realistic features simultaneously. To effectively solve the problem of global optimality, we convert this model to an equivalent set partitioning model and develop a specialized branch-and-price approach subsequently. Our approach's computational efficiency is verified via extensive numerical experiments. The model is applied to a real-world case study in Nanjing, China. Results show that incorporating the TOU electricity price into the electric bus scheduling problem can produce a sizeable cost saving of up to 22%. Managerial insights unveiled by the numerical results are discussed. These insights inform the practitioners of how the operations of electric buses can be both cost-effective and grid-friendly.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationComputer-aided civil and infrastructure engineering, 15 Apr. 2024, v. 39, no. 8, p. 1218-1237en_US
dcterms.isPartOfComputer-aided civil and infrastructure engineeringen_US
dcterms.issued2024-04-15-
dc.identifier.eissn1467-8667en_US
dc.description.validate202312 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2529-
dc.identifier.SubFormID47825-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextTransport Departmenten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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