An Electric Vehicle Migration Framework

Raqabi El Mehdi Er and Li Wenkai ()
Additional contact information
Li Wenkai: IUJ Research Institute, International University of Japan

No EMS_2022_03, Working Papers from Research Institute, International University of Japan

Abstract: Electric vehicles (EVs), with lighter environmental footprint than traditional gasoline vehicles, are growing rapidly worldwide. Some countries such as Norway and Canada have successfully established EV networks and achieved a significant progress towards EV deployment. While the EV technology is becoming popular in developed countries, emerging countries are lacking behind mainly because of the huge investment hurdle to establishing EV networks. This paper developed an efficient Electric Vehicle Migration Framework (EVMF) aiming to minimize the total costs involved in establishing an EV network, using real world data from three major cities of Morocco: Rabat, Casablanca, and Fes. A given set of public institutions having a fleet of EVs are first grouped into zones based on clustering algorithms. MILP (Mixed Integer Linear Programming) models are developed to optimally select EV charging station locations within these organizations, with an objective to minimize the total cost. This paper can help to minimize the investment needed to establish EV networks. The transition towards EV networks can first take place in cities, especially at public institutions, followed by locations among cities. With the framework developed in this paper, policy makers can make better decisions on EV network migration.

Keywords: Electric vehicle; range anxiety; public transport; optimization; MILP; data mining; remote sensing; clustering. (search for similar items in EconPapers)
Pages: 43 pages
Date: 2022-04
New Economics Papers: this item is included in nep-tre and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.iuj.ac.jp/workingpapers/index.cfm?File=EMS_2022_03.pdf First version, 2022 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iuj:wpaper:ems_2022_03

Access Statistics for this paper

More papers in Working Papers from Research Institute, International University of Japan 777 Kokusai-cho, Minami Uonuma0-shi, Niigata 949-7277 JAPAN. Contact information at EDIRC.
Bibliographic data for series maintained by Kazumi Imai, Office of Academic Affairs ().