Optimal Location of Charging Stations for Electric Vehicles in Distribution Networks: A Literature Review

David Lara Leon, Yandi Gallego Landera, Luis Garcia Santander, Lesyani Teresa León Viltre (), Oscar Cuaresma Zevallos and Fredy Antonio Muñoz Jarpa
Additional contact information
David Lara Leon: Departamento de Ingeniería Eléctrica, Universidad de Concepcion, Concepción 4070386, Chile
Yandi Gallego Landera: Departamento de Ingeniería Eléctrica y Electrónica, Universidad del Bío-Bío, Concepción 4051381, Chile
Luis Garcia Santander: Departamento de Ingeniería Eléctrica, Universidad de Concepcion, Concepción 4070386, Chile
Lesyani Teresa León Viltre: Departamento de Ingeniería Eléctrica y Electrónica, Universidad del Bío-Bío, Concepción 4051381, Chile
Oscar Cuaresma Zevallos: Electrical Engineering Department, Rio de Janeiro State University (UERJ), 524 São Francisco Xavier, Rio de Janeiro 20550-900, Brazil
Fredy Antonio Muñoz Jarpa: Departamento de Ingeniería Eléctrica y Electrónica, Universidad del Bío-Bío, Concepción 4051381, Chile

Energies, 2025, vol. 18, issue 21, 1-23

Abstract: Currently, the global use of electric vehicles is still low; however, a significant increase is expected in the coming years. Determining the optimal location of charging stations in distribution systems can influence the increased adoption of this technology in transportation, as it contributes to the proper functioning of distribution networks. There are several optimization methods, which can be classified into exact, heuristic, and metaheuristic methods, each with different characteristics and applications. This article presents a literature review of the main optimization methods currently used to determine the location of charging stations in distribution systems. It concludes that metaheuristic optimization methods are the most widely used. In addition, the review identifies current research gaps, particularly the limited use of real EV demand data and the lack of stochastic approaches to represent demand variability. The main contribution of this work lies in emphasizing the importance of incorporating stochastic methods to adequately address the uncertainty of EV demand in distribution networks.

Keywords: charging stations; electric vehicles; optimization methods; literature review (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/21/5616/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/21/5616/ (text/html)

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:gam:jeners:v:18:y:2025:i:21:p:5616-:d:1779673

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().