Development of a computational tool to evaluate the energy diversification of transportation systems in Colombia

Authors

DOI:

https://doi.org/10.14482/inde.40.02.620.986

Keywords:

Energy diversification, vehicle fleet, software engineering, JavaScript language, environmental

Abstract

There is a growing demand in energy consumption in Colombia. For this reason, the country wants to promote policies for the diversification of its energy in the transport systems. Thus, it is relevant to evaluate the energy and environmental impacts of promoting the increase of the zero and low emission vehicles. The objective of this study is to show the development of a computational tool that implements several models and allows the configuration of different technology scenarios to determine the impact of the implementation of zero and low emission vehicle fleets. To develop the tool, an agile software development methodology is used, which facilitates following a systematic process for its construction. Using the computational tool, the user can obtain results of short-, medium-, and long-term projections.

References

C. García, X. Barrera, R. Gómez, and R. Suárez, El ABC de los compromisos de Colombia para la COP21, 2nd ed. Bogotá: WWF-Colombia, 2015.

IDEAM, PNUD, MADS, and DNP, Inventario nacional y departamental de Gases Efecto Invernadero – Colombia. Tercera Comunicación Nacional de Cambio Climático. Bogotá D.C: PuntoAparte, 2016.

C. García Arbeláez, G. Vallejo, M. L. Higgings, and E. M. Escobar, El Acuerdo de París. Así actuará Colombia frente al cambio climático, 1st ed. Bogotá D.C: WWF-Colombia, 2016.

Organización Mundial de la Salud, “Calidad del aire ambiente (exterior) y salud,” 2018. https://www.who.int/es/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health (accessed Aug. 11, 2021).

Dirección Nacional de Planeación, “Valoración económica de la degradación ambiental en Colombia.” DNP, 2015.

J. de D. Ortuzar and L. G. Willumsen, Modelling Transport, 4th ed. Chichester, West Sussex, United Kingdom: Wiley, 2011.

R. Kitamura and M. Kuwahara, Eds., Simulation Approaches in Transportation Analysis: Recent Advances and Challenges. German: Springer US, 2005. doi: 10.1007/b104513.

C. Linton, S. Grant-Muller, and W. Gale, “Approaches and Techniques for Modelling CO 2 Emissions from Road Transport,” Transport Reviews, vol. 35, no. 4, pp. 1–21, Apr. 2015, doi: 10.1080/01441647.2015.1030004.

P. Pfaffenbichler, Mars - Metropolitan Activity Relocation Simulator. German: VDM Verlag, 2009. Accessed: Sep. 15, 2021. [Online]. Available: http://www.ivv.tuwien.ac.at/forschung/ mars-metropolitan-activity-relocation-simulator.html

S. H. Kim, J. Edmonds, J. Lurz, S. J. Smith, and M. Wise, “The objECTS Framework for integrated Assessment: Hybrid Modeling of Transportation,” The Energy Journal, vol. Hybrid Modeling, no. Special Issue #2, pp. 63–92, 2006.

U.S. Energy Information Administration (EIA), “World Energy Projection System Plus: Overview,” 2017. https://www.eia.gov/analysis/pdfpages/wepsoverviewindex.php (accessed Sep. 15, 2021).

C. H. Song and L. J. Aaldering, “Strategic intentions to the diffusion of electric mobility paradigm: The case of internal combustion engine vehicle,” Journal of Cleaner Production, vol. 230, pp. 898–909, Sep. 2019, doi: 10.1016/j.jclepro.2019.05.126.

R. Gupta, C. Mejia, Y. Gianchandani, and Y. Kajikawa, “Analysis on formation of emerging business ecosystems from deals activities of global electric vehicles hub firms,” Energy Policy, vol. 145, p. 111532, Oct. 2020, doi: 10.1016/j.enpol.2020.111532.

L. Poon, “How China Took Charge of the Electric Bus Revolution,” Bloomberg - City Lab, May 2018. https://www.bloomberg.com/news/articles/2018-05-08/in-china-shenzhen-electrified-its-entire-bus-fleet (accessed Aug. 13, 2021).

MinAmbiente, MinTransporte, and Upme, Estrategia Nacional de Movilidad Eléctrica. Bogotá: Ministerio de Ambiente y Desarrollo Sostenible, 2020.

ANDI and FENALCO, “Informe de vehículos eléctricos e híbridos,” ANDI, Bogotá, 2021.

J. L. Kirk, A. L. Bristow, and A. M. Zanni, “Exploring the market for Compressed Natural Gas light commercial vehicles in the United Kingdom,” Transportation Research Part D: Transport and Environment, vol. 29, pp. 22–31, Jun. 2014, doi: 10.1016/j.trd.2014.03.004.

Dft, Action for Roads: A Network for the 21st Century. London: Departament for Transport, 2013.

M. I. Khan, T. Yasmin, and A. Shakoor, “Technical overview of compressed natural gas (CNG) as a transportation fuel,” Renewable and Sustainable Energy Reviews, vol. 51, pp. 785–797, Nov. 2015, doi: 10.1016/j.rser.2015.06.053.

IDAE, “Combustibles y vehículos alternativos,” IDAE Instituto para la Diversificación y Ahorro de la Energía, Cataluña, 2005.

O. US EPA, “MOVES and Other Mobile Source Emissions Models,” Feb. 12, 2016. https://www.epa.gov/moves (accessed Aug. 17, 2021).

EMISIA, “COPERT - The industry standard emissions calculator,” 2019. https://www.emisia.com/utilities/copert/ (accessed Aug. 17, 2021).

P. G. Gipps, “A behavioural car-following model for computer simulation,” Transportation Research Part B: Methodological, vol. 15, no. 2, pp. 105–111, Apr. 1981, doi: 10.1016/0191-2615(81)90037-0.

R. S. Pressman, Ingeniería del Software. Un enfoque práctico, 7th ed. México: Mc Graw-Hill, 2010.

A. Weitzenfeld, Ingeniería del software orientada a objetos con UML, Java e Internet. México: Thomson, 2005.

P. Letelier and M. C. Penadés, “Métodologías ágiles para el desarrollo de software: eXtreme Programming (XP),” Técnica administrativa, vol. 5, no. 26, p. 1, 2006.

I. Sommerville, Software Engineering, 9th ed. USA: Pearson Educación S.A, 2010.

R. Liu, D. Vilet, and D. Watling, “DRACULA: DYNAMIC ROUTE ASSIGNMENT COMBINING USER LEARNING AND MICROSIMULATION,” London, 2015, vol. E, pp. 143–152.

E. Stern and H. RICHARDSON, “Behavioural modelling of road users: Current research and future needs,” Transport Reviews - TRANSP REV, vol. 25, pp. 159–180, Mar. 2005, doi: 10.1080/0144164042000313638.

A. Horni, K. Nagel, and K. Axhausen, Eds., The Multi-Agent Transport Simulation MATSim. London: Ubiquity Press, 2016. doi: 10.5334/baw.

W. Rothengatter et al., “ASTRA - assessment of transport strategies,” Karlsruhe: Commission of the European Communities, 2000.

P. Pfaffenbichler, “The strategic, dynamic and integrated urban land use and transport model MARS (Metropolitan Activity Relocation Simulator): development, testing and application /,” University of Natural Resources and Life Sciences Vienna, Vienna, 2003.

Published

2022-07-04

How to Cite

[1]
J. C. Blandón Andrade, K. E. Castaño Gil, and J. E. Tibaquirá Giraldo, “Development of a computational tool to evaluate the energy diversification of transportation systems in Colombia”, Ing. y Des., vol. 40, no. 2, pp. 166–186, Jul. 2022.