The charging station location problem with photovoltaic systems: A case study

El problema de la localización de estaciones de recarga con sistemas fotovoltaicos: Un caso de estudio

Published 2022-12-20

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Vol. 20 No. 39 (2023): Table of contents Revista EIA No. 39
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The charging station location problem with photovoltaic systems: A case study. (2022). Revista EIA, 20(39), 3914 pp. 1-25. https://doi.org/10.24050/reia.v20i39.1627
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Alejandro Uribe
Universidad EAFIT, Colombia.
https://orcid.org/0000-0002-0761-6655
Andrés Felipe Tamayo Ángel
Purchasing Coordinator Eiffage Canada Inc
Camilo Vélez Gómez
Ingeniero de datos en Factored A.I., Estados Unidos
Jose Alejandro Montoya Echeverry
Universidad EAFIT, Colombia.
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In recent years there is the tendency to charge Electric Vehicles (EVs) with clean sources of energy. Due to this tendency, scientific literature focused on problems of locating and sizing Photovoltaic (PV) Charging Stations (CSs). In this paper, we studied the case of the localization and sizing of PV powered CSs in the region of Valle de Aburrá, Colombia, which is the region of the country with the fastest growth of EV adoption. Looking to utilize the largest amount of PV power, we considered Level 1 (low-power) PV-grid CSs. The use of other PV charging systems, like level 3 (high-power) charging, would require covering bigger roof areas with PV panels, more than the available on an urban landscape. Considering that this problem takes into account low-power CSs, candidate CS locations are places where people go for extended periods of time, with large roof areas and parking availability. In this problem, the decision variables are the location of the CSs, the amount of charging spots at each selected location, and the size of the PV system. These decisions aim to minimize the added annualized cost of the PV systems, the annualized cost of the charging spots in the selected CSs, and the cost of energy purchased from the grid in a year. For calculating the amount of power that the PV systems are capable of generating, we obtained the typical irradiation curves for each candidate CS location. For solving the studied problem, we propose a Mixed Integer Linear Programming (MILP) formulation.

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