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Conference Paper: A novel evaluation method of electric vehicles charging network based on stochastic geometry

TitleA novel evaluation method of electric vehicles charging network based on stochastic geometry
Authors
Keywordscharging stations planning
electric vehicles (EVs)
stochastic geometry
vehicular network
SINR
Issue Date2020
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800214
Citation
2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, 26-28 October 2020, p. 464-468 How to Cite?
AbstractThe randomness, mobility and dispersion of electric vehicles (EVs) charging bring great challenges to the planning of charging network. For EV users with range anxiety, the existing charging network has the disadvantages of low coverage, high damage rate and irrational configuration. In this paper, an evaluation method of EV charging network based on stochastic geometry is introduced with taking the charging demand of EV users and vehicular networking communication into consideration. Firstly, a heterogeneous charging network consists of different types of charging facilities is constructed based on Voronoi diagram. Then the SINR model is utilized to analyze theoretically the system-level performance of charging network. We derive the closed-form expression of coverage probability based on mathematical tools of stochastic geometry. The numerical experiments are performed, and simulation results show the rationality of the proposed method.
Persistent Identifierhttp://hdl.handle.net/10722/305967
ISBN

 

DC FieldValueLanguage
dc.contributor.authorREN, C-
dc.contributor.authorHou, Y-
dc.date.accessioned2021-10-20T10:16:55Z-
dc.date.available2021-10-20T10:16:55Z-
dc.date.issued2020-
dc.identifier.citation2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, 26-28 October 2020, p. 464-468-
dc.identifier.isbn9781728171012-
dc.identifier.urihttp://hdl.handle.net/10722/305967-
dc.description.abstractThe randomness, mobility and dispersion of electric vehicles (EVs) charging bring great challenges to the planning of charging network. For EV users with range anxiety, the existing charging network has the disadvantages of low coverage, high damage rate and irrational configuration. In this paper, an evaluation method of EV charging network based on stochastic geometry is introduced with taking the charging demand of EV users and vehicular networking communication into consideration. Firstly, a heterogeneous charging network consists of different types of charging facilities is constructed based on Voronoi diagram. Then the SINR model is utilized to analyze theoretically the system-level performance of charging network. We derive the closed-form expression of coverage probability based on mathematical tools of stochastic geometry. The numerical experiments are performed, and simulation results show the rationality of the proposed method.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800214-
dc.relation.ispartofIEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)-
dc.rightsIEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe). Copyright © IEEE.-
dc.rights©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectcharging stations planning-
dc.subjectelectric vehicles (EVs)-
dc.subjectstochastic geometry-
dc.subjectvehicular network-
dc.subjectSINR-
dc.titleA novel evaluation method of electric vehicles charging network based on stochastic geometry-
dc.typeConference_Paper-
dc.identifier.emailHou, Y: yhhou@hku.hk-
dc.identifier.authorityHou, Y=rp00069-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISGT-Europe47291.2020.9248842-
dc.identifier.scopuseid_2-s2.0-85097352453-
dc.identifier.hkuros327416-
dc.identifier.spage464-
dc.identifier.epage468-
dc.publisher.placeUnited States-

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