Determinant Factors in Estimating Charging Stations for Electric Vehicles in Bogotá Using Voronoi Regions

This study presents a methodological model for planning the locations of electric vehicle (EV) charging stations in Bogotá, using spatial statistical methods and tools that analyze the variables influencing such planning. The research focuses on dividing the city into zones based on the 37 EV charging stations active as of February 2024, applying the Voronoi polygon theory. Data on population, road networks, and mobility patterns within each zone were collected to create maps and conduct detailed analysis. The results indicate that the current distribution of charging stations follows identifiable spatial patterns, allowing trends in their placement to be observed. These insights support the formulation of strategic plans to optimize station distribution and help estimate the resources needed to develop an efficient electric mobility infrastructure in the city.

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Publication Details

Journal
Ciencia e Ingeniería Neogranadina
Published
2025-10-22
DOI
https://doi.org/10.18359/rcin.7763
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Determinant Factors in Estimating Charging Stations for Electric Vehicles in Bogotá Using Voronoi Regions

Ciencia e Ingeniería Neogranadina
Prenatal Screening and Diagnostics
article

Determinant Factors in Estimating Charging Stations for Electric Vehicles in Bogotá Using Voronoi Regions

article en

Abstract

This study presents a methodological model for planning the locations of electric vehicle (EV) charging stations in Bogotá, using spatial statistical methods and tools that analyze the variables influencing such planning. The research focuses on dividing the city into zones based on the 37 EV charging stations active as of February 2024, applying the Voronoi polygon theory. Data on population, road networks, and mobility patterns within each zone were collected to create maps and conduct detailed analysis. The results indicate that the current distribution of charging stations follows identifiable spatial patterns, allowing trends in their placement to be observed. These insights support the formulation of strategic plans to optimize station distribution and help estimate the resources needed to develop an efficient electric mobility infrastructure in the city.

Ciencia e Ingeniería NeogranadinaVol. 35(2)
Universidad Distrital Francisco José de Caldas (CO)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Prenatal Screening and Diagnostics
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