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

dc.creatorPantoja Benavidez, Jaime Francisco
dc.creatorRodríguez Patarroyo, Diego Julián
dc.creatorSalamanca Bernal, Julián Andrés
dc.date2025-10-22
dc.date.accessioned2025-12-19T17:28:01Z
dc.date.available2025-12-19T17:28:01Z
dc.descriptionThis 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.en-US
dc.descriptionEste estudio presenta un modelo metodológico para planificar ubicaciones de estaciones de carga de vehículos eléctricos en Bogotá donde se hace uso de métodos y herramientas de la estadística espacial de variables estadísticas que influyen en dicha planificación. El estudio se centra en dividir la ciudad en zonas según las 37 estaciones de carga para vehículos eléctricos (VE) activas hasta febrero de 2024 utilizando la teoría de polígonos de Voronoi. La información recopilada para el estudio sobre la población, infraestructura vial y la movilidad de cada zona permite elaborar mapas y poder así analizar la información. Los resultados del estudio muestran que la distribución actual de las estaciones de carga sigue ciertos patrones, lo que permite identificar tendencias en su ubicación. Esto facilita la formulación de planes y estrategias para mejorar su distribución, así como la proyección de los recursos necesarios para el desarrollo de una infraestructura de movilidad eléctrica eficiente en la ciudad.es-ES
dc.descriptionEste estudo apresenta um modelo metodológico para planejar a localização de estações de recarga de veículos elétricos em Bogotá, fazendo uso de métodos e ferramentas da estatística espacial de variáveis estatísticas que influenciam esse planejamento. O estudo concentra-se em dividir a cidade em zonas a partir das 37 estações de recarga para veículos elétricos (VE) ativas até fevereiro de 2024, utilizando a teoria dos polígonos de Voronoi. As informações coletadas para o estudo sobre a população, a infraestrutura viária e a mobilidade de cada zona permitem elaborar mapas e, assim, analisar os dados. Os resultados do estudo mostram que a distribuição atual das estações de recarga segue certos padrões, o que permite identificar tendências em sua localização. Isso facilita a formulação de planos e estratégias para melhorar sua distribuição, bem como a projeção dos recursos necessários para o desenvolvimento de uma infraestrutura de mobilidade elétrica eficiente na cidade.pt-BR
dc.formatapplication/pdf
dc.identifierhttps://revistas.umng.edu.co/index.php/rcin/article/view/7763
dc.identifier10.18359/rcin.7763
dc.identifier.urihttps://dspace7.infotegra.com/dspace7demo/45360
dc.languageeng
dc.publisherUniversidad Militar Nueva Granadaes-ES
dc.relationhttps://revistas.umng.edu.co/index.php/rcin/article/view/7763/6669
dc.relation/*ref*/A. Brown, A. Cappellucci, E. White, A. Heinrich y E. Cost, Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Second Quarter 2023, National Renewable Energy Laboratory, NREL/TP-5400-87033, 2023, DOI: https://doi.org/10.2172/2203059
dc.relation/*ref*/Molina et al., “Application of geostatistical techniques and their integration with tools such as geographic information systems (GIS),” 2021.
dc.relation/*ref*/Guzman et al., “The optimal location of EV charging stations is a pivotal factor in facilitating their adoption,” 2023.
dc.relation/*ref*/M. S. Hossain et al., “A Comprehensive Review on the Integration of Electric Vehicles for Sustainable Development,” Journal of Advanced Transportation, vol. 2022, 11 Oct. 2022. DOI: https://doi.org/10.1155/2022/3868388
dc.relation/*ref*/K. P. C. D. Cruz y L. K. S. Tolentino, “Unlocking the market potential of electric vehicles in the Philippines: A statistical and neural network approach to customer willingness to purchase electric vehicles,” International Journal of Innovative Research and Scientific Studies, vol. 6, no. 4, pp. 888–902, 2023. [En línea]. Disponible: https://www.ijirss.com/index.php/ijirss/article/download/2088/397/3379
dc.relation/*ref*/Omahne et al., “Social aspects of electric vehicles research—trends and relations to sustainable development goals,” World Electric Vehicle Journal, vol. 12, no. 1, p. 15, 2021, DOI: https://doi.org/10.3390/wevj12010015
dc.relation/*ref*/Bernal-Vargas et al., “Prospective analysis of massive integration of electric vehicle chargers and their impact on power quality in distribution networks,” World Electric Vehicle Journal, vol. 14, no. 12, p. 324, 2023, DOI: https://doi.org/10.3390/wevj14120324
dc.relation/*ref*/Mojumder et al., “Electric vehicle-to-grid (V2G) technologies: Impact on the power grid and battery,” Sustainability, vol. 14, no. 21, p. 13856, 2022, DOI: https://doi.org/10.3390/su142113856
dc.relation/*ref*/A. Rabie, A. Ghanem, S. S. Kaddah y M. M. El-Saadawi, “Enhancing the performance of radial distribution systems via optimal integration of electric vehicles,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 14, no. 4, pp. 2514–2526, diciembre 2023, DOI: https://doi.org/10.11591/ijpeds.v14.i4.pp2514-2526
dc.relation/*ref*/Y. Zhang, Y. Wang, F. Li, B. Wu, Y.-Y. Chiang y X. Zhang, “Efficient deployment of electric vehicle charging infrastructure: Simultaneous optimization of charging station placement and charging pile assignment,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 11, pp. 6654–6659, 2021. [Online].DOI: https://doi.org/10.1109/TITS.2020.2990694
dc.relation/*ref*/B. Javed, M. Kandlikar y A. Giang, “Variability in costs of electrifying passenger cars in Canada,” Environmental Research: Infrastructure and Sustainability, vol. 4, no. 1, Art. 015008, 2024.
dc.relation/*ref*/Unterluggauer et al., “Electric vehicle charging infrastructure planning for integrated transportation and power distribution networks: A review,” eTransportation, vol. 12, p. 100163, 2022, DOI: https://doi.org/10.1016/j.etran.2022.100163
dc.relation/*ref*/Sadeghian et al., “A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges,” Journal of Energy Storage, vol. 54, p. 105241, 2022, DOI:1 https://doi.org/0.1016/j.est.2022.105241
dc.relation/*ref*/S. Erdoğan, İ. Çapar, İ. Çapar y M. M. Nejad, “Establishing a statewide electric vehicle charging station network in Maryland: A corridor-based station location problem,” Socio-Economic Planning Sciences, vol. 79, p. 101127, 2022.
dc.relation/*ref*/S. Alkhalisi, “Creating a qualitative typology of electric vehicle driving: EV journey-making mapped in a chronological framework,” Transportation Research Part F: Traffic Psychology and Behaviour, vol. 69, pp. 159–186, 2020, DOI: https://doi.org/10.1016/j.trf.2020.01.009
dc.relation/*ref*/Feng et al., “Review of electric vehicle charging demand forecasting based on multi-source data,” in 2020 IEEE Sustainable Power and Energy Conference (iSPEC), pp. 139–146, 2020. [Online]. Disponible: DOI https://doi.org/10.1109/iSPEC50848.2020.9351008
dc.relation/*ref*/Janjić et al., “Estimating the optimal number and locations of electric vehicle charging stations: The application of multi-criteria p-median methodology,” Transportation Planning and Technology, vol. 44, no. 8, pp. 827–842, 2021, DOI: https://doi.org/10.1080/03081060.2021.1992177
dc.relation/*ref*/A. Llopis Herrero, Desarrollo de un simulador de carga de vehículos eléctricos a nivel interurbano, Tesis doctoral, Universitat Politecnica de Valencia, 2023. [En linea]. Disponible: https://hdl.handle.net/10251/192785
dc.relation/*ref*/Arias et al., Estadística espacial: Fundamentos y aplicación con sistemas de información geográfica. Ciudad Autonoma de Buenos Aires: Impresiones Buenos Aires, 2021.
dc.relation/*ref*/G. Buzai, “Areas de influencia de los centros de atencion primaria de salud (CAPS) en la ciudad de Lujan mediante poligonos de Voronoi-Thiessen,” Instituto de Investigaciones Geograficas, 2016. [En linea]. Disponible: https://hdl.handle.net/11336/118055
dc.relation/*ref*/N. C. Principi, Análisis de la estructura socioespacial regional: Aplicación de Sistemas de Información Geográfica (SIG) al noroeste de la Provincia de Buenos Aires (Argentina). Editorial Academica Espanola, 2013.
dc.relation/*ref*/Departamento Administrativo Nacional de Estadistica (DANE), “Estratificacion socioeconomica urbana para servicios publicos domiciliarios,” 2015. [En linea]. Disponible: https://www.dane.gov.co/files/geoestadistica/estratificacion/ManualdeRealizacion.pdf
dc.relation/*ref*/ENEL, Puntos de recarga de vehículos eléctricos, Enel Colombia SA ESP, 2022.
dc.relation/*ref*/Electromaps, “Puntos de carga en Bogota – base de datos (7 estaciones en Bogota; punto mas reciente: WorkMates Masterline, anadido el 18 12 2024),” Electromaps, 2025. [En linea]. Disponible: https://www.electromaps.com/es/puntos-carga/colombia/bogota
dc.relation/*ref*/Enel X, “Nueva estacion de carga en Centro Comercial Unicentro Bogota (4 espacios; 60 kW, 30 kW y 30 kW),” Enel X, mar. 2025. [En linea]. Disponible: https://www.enelx.com/co/es/historias/nueva-estacion-de-carga-unicentro
dc.relation/*ref*/Terpel Voltex, “Infraestructura de recarga para movilidad electrica – Corporativo Bogota (Carrera 7 No. 75 51),” Terpel, 2025. [En linea]. Disponible: https://www.terpel.com/nueva-movilidad-y-energias/terpel-voltex
dc.relation/*ref*/Dielco, “Mapa de electrolineras Dielco – estaciones de recarga en Bogota,” Electrolineras Dielco, 2025. [En linea]. Disponible: https://electrolineras.dielco.co/
dc.relation/*ref*/J. A. Piraquive Rodriguez y D. E. Dimate Mora, “La eficacia de los presupuestos participativos en la localidad de Sumapaz a nivel local,” 2024.
dc.relation/*ref*/DANE, “Geoportal,” 2024. [En linea]. Disponible: https://geoportal.dane.gov.co/#gsc.tab=0
dc.relation/*ref*/Alcaldia Mayor de Bogota, Bogotá mi ciudad, 2024a.
dc.relation/*ref*/Alcaldia Mayor de Bogota, Datos abiertos Bogotá, 2024b.
dc.relation/*ref*/OpenStreetMap contributors, “OpenStreetMap: The free wiki world map,” 2024. [En linea]. Disponible: https://www.openstreetmap.org
dc.relation/*ref*/DANE, “Boletin Tecnico ECV 2021,” 2024. [En linea]. Disponible: https://www.dane.gov.co/files/investigaciones/condiciones_vida/calidad_vida/2021/Boletin_Tecnico_ECV_2021.pdf
dc.relation/*ref*/Free Software Foundation, “GNU General Public License, Version 3,” 2007. [En linea]. Disponible: https://www.gnu.org/licenses/gpl-3.0.html
dc.relation/*ref*/G. D. Buzai y E. J. Montes Galvan, Estadística espacial: Fundamentos y aplicación con sistemas de información geográfica. Universidad Nacional de Lujan, Instituto de Investigaciones Geograficas, 2021.
dc.relation/*ref*/S. Li, O. Gao y F. You, “AI for Science in Electrochemical Energy Storage: A Multi-Scale Systems Perspective on Transportation Electrification,” Nexus, 2024.
dc.relation/*ref*/D. Toro Gonzalez, V. M. Cantillo Maza y A. Espinosa Espinosa, “La demanda de transporte publico en Colombia, 2000-2010,” 2018.
dc.relation/*ref*/E. Guerra, “The built environment and car use in Mexico City: Is the relationship changing over time,” Journal of Planning Education and Research, vol. 34, no. 4, pp. 394–408, 2014.
dc.relation/*ref*/H. R. Sayarshad, “Optimization of electric charging infrastructure: integrated model for routing and charging coordination with power-aware operations,” npj Sustainable Mobility and Transport, vol. 1, no. 1, Art. 4, 2024.
dc.relation/*ref*/F. Hao, “Impact of electric vehicle charging demand on clean energy regional power grid control,” Energy Informatics, vol. 8, no. 1, p. 1, 2025.
dc.rightsDerechos de autor 2025 Ciencia e Ingeniería Neogranadinaes-ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0es-ES
dc.sourceCiencia e Ingenieria Neogranadina; Vol. 35 No. 2 (2025); 141 - 160en-US
dc.sourceCiencia e Ingeniería Neogranadina; Vol. 35 Núm. 2 (2025); 141 - 160es-ES
dc.sourceCiencia e Ingeniería Neogranadina; v. 35 n. 2 (2025); 141 - 160pt-BR
dc.source1909-7735
dc.source0124-8170
dc.subjectCharging stationsen-US
dc.subjectElectric Vehiclesen-US
dc.subjectVoronoi zonesen-US
dc.subjectestaciones de cargaes-ES
dc.subjectvehículos eléctricoses-ES
dc.subjectzonas de Voronoies-ES
dc.subjectestações de recargapt-BR
dc.subjectveículos elétricospt-BR
dc.subjectregiões de Voronoipt-BR
dc.titleDeterminant Factors in Estimating Charging Stations for Electric Vehicles in Bogotá Using Voronoi Regionsen-US
dc.titleFactores determinantes en la estimación de estaciones de carga para vehículos eléctricos en Bogotá, utilizando Regiones de Voronoies-ES
dc.titleFatores Determinantes na Estimativa de Estações de Recarga para Veículos Elétricos em Bogotá Utilizando Regiões de Voronoipt-BR
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

Archivos