Optimizing Public Charging: An Integrated Approach Based on GIS and Multi-Criteria Decision Analysis

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dc.contributor.authorKhalife, Ali
dc.contributor.authorFay, Tu-Anh
dc.contributor.authorGöhlich, Dietmar
dc.date.accessioned2022-08-09T13:21:58Z
dc.date.available2022-08-09T13:21:58Z
dc.date.issued2022-07-25
dc.date.updated2022-08-03T11:28:08Z
dc.description.abstractThe rise in electric vehicle uptake has reshaped the German mobility landscape at unprecedented speed and scale. While public charging is pivotal to growing the electric vehicle market, municipalities can play a crucial role in accelerating the energy transition in transport. This research aims to assist municipalities in planning their strategic rollouts of public charging infrastructure in size and location. In the first step, charging demand is estimated based on four development scenarios in 2030 of EV adoption and public charging. In a second step, a geospatial analysis was performed on the study area. Supply and demand criteria were considered to reflect the attractiveness of each location on a grid map. While the supply criteria represent constraints related to infrastructure availability, the demand criteria are categorized into three dimensions: residential, commercial, and leisure. The prioritization of demand criteria was derived from the municipality’s input using the analytical hierarchy process method to reflect its strategy. After obtaining the suitability index map, a cluster analysis was performed using a k-means clustering algorithm to ensure adequate geographical coverage of the charging network. Finally, the proposed charging stations in each scenario were allocated to the top-scoring locations, establishing a municipal public charging network.en
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2022en
dc.identifier.eissn2032-6653
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/17317
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-16098
dc.language.isoenen
dc.rightsLicensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc620 Ingenieurwissenschaften und zugeordnete Tätigkeitende
dc.subject.otherelectric vehiclesen
dc.subject.otherpublic charging infrastructure planningen
dc.subject.othermunicipal planningen
dc.subject.othercharging demanden
dc.subject.othermulti-criteria decision makingen
dc.subject.otheranalytical hierarchy processen
dc.subject.othergeospatial analysisen
dc.subject.othergeographic information systemsen
dc.titleOptimizing Public Charging: An Integrated Approach Based on GIS and Multi-Criteria Decision Analysisen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber131en
dcterms.bibliographicCitation.doi10.3390/wevj13080131en
dcterms.bibliographicCitation.issue8en
dcterms.bibliographicCitation.journaltitleWorld Electric Vehicle Journalen
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume13en
tub.accessrights.dnbfreeen
tub.affiliationFak. 5 Verkehrs- und Maschinensysteme>Inst. Maschinenkonstruktion und Systemtechnik>FG Methoden der Produktentwicklung und Mechatronikde
tub.affiliation.facultyFak. 5 Verkehrs- und Maschinensystemede
tub.affiliation.groupFG Methoden der Produktentwicklung und Mechatronikde
tub.affiliation.instituteInst. Maschinenkonstruktion und Systemtechnikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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