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Optimal placement of charging stations for electric vehicles in large-scale transportation networks
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Malmö Högskola, SWE.
2019 (English)In: Procedia Computer Science, Elsevier B.V. , 2019, Vol. 160, p. 77-84Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a new practical approach to optimally allocate charging stations in large-scale transportation networks for electric vehicles (EVs). The problem is of particular importance to meet the charging demand of the growing fleet of alternative fuel vehicles. Considering the limited driving range of EVs, there is need to supply EV owners with accessible charging stations to reduce their range anxiety. The aim of the Route Node Coverage (RNC) problem, which is considered in the current paper, is to find the minimum number of charging stations, and their locations in order to cover the most probable routes in a transportation network. We propose an iterative approximation technique for RNC, where the associated Integer Problem (IP) is solved by exploiting a probabilistic random walk route selection, and thereby taking advantage of the numerical stability and efficiency of the standard IP software packages. Furthermore, our iterative RNC optimization procedure is both pertinent and straightforward to implement in computer coding and the design technique is therefore highly applicable. The proposed optimization technique is applied on the Sioux-Falls test transportation network, and in a large-scale case study covering the southern part of Sweden, where the focus is on reaching the maximum coverage with a minimum number of charging stations. The results are promising and show that the flexibility, smart route selection, and numerical efficiency of the proposed design technique, can pick out strategic locations for charging stations from thousands of possible locations w ithout numerical difficulties. ©2019 Hie Authors. Published by Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier B.V. , 2019. Vol. 160, p. 77-84
Keywords [en]
Charging stations, Clectric vehicle, Optimal placement, Route node coverage, Transportation network, Charging (batteries), Data communication systems, Efficiency, Electric vehicles, Fleet operations, Health care, Internet protocols, Iterative methods, Location, Alternative fuel vehicles, Charging station, Iterative approximations, Large-scale transportation, Node coverage, Optimal placements, Optimization techniques, Transportation routes
National Category
Transport Systems and Logistics Energy Systems
Identifiers
URN: urn:nbn:se:bth-19238DOI: 10.1016/j.procs.2019.09.446ISI: 000515510100010Scopus ID: 2-s2.0-85079099240OAI: oai:DiVA.org:bth-19238DiVA, id: diva2:1394942
Conference
10th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2019 and 9th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH 2019, Affiliated Workshops; Coimbra; Portugal; 4 November
Note

open access

Available from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-03-19

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Fredriksson, HenrikDahl, Mattias

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67891011129 of 14
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