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Articles

A systematic review of charging infrastructure location problem for electric vehicles

ORCID Icon, , , &
Pages 432-455 | Received 22 May 2020, Accepted 12 Nov 2020, Published online: 10 Dec 2020
 

ABSTRACT

With the evolving demand for sustainable mobility, adequate charging infrastructure for electric vehicles (EVs) has been growing steadily and wireless power transfer (WPT) technology has been seen as an efficient alternative for EV charging while maintaining seamless traffic flow. This paper reviews the modelling challenges in terms of both static (plug-in) charging (SC) and wireless charging (WC) facilities in a transportation network in terms of system integration, focusing on the evolution of the WPT technology. The first part of the paper provides an overview of all the major progress and achievements made by different research organisations in the area of WPT technology for EV charging. These technologies are ranked based on two indices, namely technological readiness level and system readiness level. The optimal location of WC facilities comes with more design and operational issues than conventional static charging facilities. However, they are similar in terms of the infrastructure modelling approach to locate these charging facilities, as the overall goal is to maximise the network flow and minimise the overall system cost. The second part of the paper assesses different modelling approaches used to analyse the network and locate the charging infrastructure for static and WC facilities. The economic feasibility of the technology is an important consideration for successful system integration as well as the overall performance of the system. As such, this paper also provides a synopsis of different socio-economic studies related to the WC infrastructure allocation problem. Finally, future research directions in this field are discussed based on the knowledge gaps identified from the existing literature.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Ministry of Business, Innovation and Employment: [Grant Number 3714101].

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