Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/87860
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorZhuge, CX-
dc.creatorWei, BR-
dc.creatorShao, CF-
dc.creatorShan, YL-
dc.creatorDong, CJ-
dc.date.accessioned2020-08-19T06:27:50Z-
dc.date.available2020-08-19T06:27:50Z-
dc.identifier.issn0301-4215-
dc.identifier.urihttp://hdl.handle.net/10397/87860-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Zhuge, C. X. , Wei, B. R. , Shao, C. F. , Shan, Y. L. , & Dong, C. J. (2020). The role of the license plate lottery policy in the adoption of electric vehicles: a case study of beijing. Energy Policy, 139, 111328, 1-18 is available at https://dx.doi.org/10.1016/j.enpol.2020.111328en_US
dc.subjectLicense plate lottery policyen_US
dc.subjectElectric vehicleen_US
dc.subjectMarket penetrationen_US
dc.subjectAgent-based modellingen_US
dc.subjectSpatial analysisen_US
dc.subjectSelfSimen_US
dc.titleThe role of the license plate lottery policy in the adoption of electric vehicles : a case study of beijingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage18-
dc.identifier.volume139-
dc.identifier.doi10.1016/j.enpol.2020.111328-
dcterms.abstractPolicy is an influential factor to the purchase and usage of Electric Vehicles (EVs). This paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in Beijing, China. An agent-based spatial integrated urban model, SelfSim-EV, is employed to investigate how the policy may influence the uptake of EVs over time at the individual level. Two types of "what-if' scenario were set up to explore how the methods to allocate the vehicle purchase permits and the number of permits might influence the EV market expansion from 2016 to 2020. The results suggested that 1) both the allocation methods and the number of purchase permits could heavily influence the uptake of EVs and further its impacts on vehicular emissions, energy consumption and urban infrastructures; 2) compared to the baseline, both scenarios got significantly different spatial distributions of vehicle owners, transport facilities, vehicular emissions and charging demand at the multiple resolutions; 3) SelfSim-EV was found as a useful tool to quantify the nonlinear relationships between the increase of EV purchasers and the demand for transport facilities and electricity, and also to capture some unexpected results coming out from the interactions in the complex dynamic urban system.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy policy, Apr. 2020, v. 139, 111328, p. 1-18-
dcterms.isPartOfEnergy policy-
dcterms.issued2020-04-
dc.identifier.isiWOS:000528255000036-
dc.identifier.scopus2-s2.0-85079240943-
dc.identifier.artn111328-
dc.description.validate202008 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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