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Article: Charging network planning for electric bus cities: A case study of Shenzhen, China

TitleCharging network planning for electric bus cities: A case study of Shenzhen, China
Authors
KeywordsPower grid
Charging station
Electric bus
Location
Transportation network
Issue Date2019
Citation
Sustainability (Switzerland), 2019, v. 11, n. 17, article no. 4713 How to Cite?
AbstractIn 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a "No R" algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.
Persistent Identifierhttp://hdl.handle.net/10722/296201
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLin, Yuping-
dc.contributor.authorZhang, Kai-
dc.contributor.authorShen, Zuo Jun Max-
dc.contributor.authorMiao, Lixin-
dc.date.accessioned2021-02-11T04:53:03Z-
dc.date.available2021-02-11T04:53:03Z-
dc.date.issued2019-
dc.identifier.citationSustainability (Switzerland), 2019, v. 11, n. 17, article no. 4713-
dc.identifier.urihttp://hdl.handle.net/10722/296201-
dc.description.abstractIn 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a "No R" algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.-
dc.languageeng-
dc.relation.ispartofSustainability (Switzerland)-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectPower grid-
dc.subjectCharging station-
dc.subjectElectric bus-
dc.subjectLocation-
dc.subjectTransportation network-
dc.titleCharging network planning for electric bus cities: A case study of Shenzhen, China-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/su11174713-
dc.identifier.scopuseid_2-s2.0-85071992676-
dc.identifier.volume11-
dc.identifier.issue17-
dc.identifier.spagearticle no. 4713-
dc.identifier.epagearticle no. 4713-
dc.identifier.eissn2071-1050-
dc.identifier.isiWOS:000486877700201-

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