Geographical information systems as a Tool to assist the electricity distribution Networks planning

ABSTRACT. In recent years, the population growth in urban areas of Latin American cities has resulted in an increase in demand for electricity in a dispersed manner, bringing challenges to the planning of distribution systems to supply this demand. In addition, incentives for the installation of dis...

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Autores:
Mejia Alzate, Mario Andres
Melo Trujillo, Joel David
Padilha Feltrin, Antonio
Sánchez Zuleta, Carmen Cecilia
Fernández Gutiérrez, Juan Pablo
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Universidad EIA .
Repositorio:
Repositorio EIA .
Idioma:
eng
OAI Identifier:
oai:repository.eia.edu.co:11190/5009
Acceso en línea:
https://repository.eia.edu.co/handle/11190/5009
https://doi.org/10.24050/reia.v15i29.1138
Palabra clave:
Planificación del Sistema de Distribución
Sistemas de Información Geográfica
Geo procesamiento
Análisis Espacial
Características Socioeconómicas
sistemas de distribución de energia eléctrica
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openAccess
License
Revista EIA - 2018
id REIA2_fcdb42af1425ffa15a987d28230bd406
oai_identifier_str oai:repository.eia.edu.co:11190/5009
network_acronym_str REIA2
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repository_id_str
dc.title.spa.fl_str_mv Geographical information systems as a Tool to assist the electricity distribution Networks planning
dc.title.translated.eng.fl_str_mv Geographical Information Systems as a Tool to Assist the Electricity Distribution Networks Planning
title Geographical information systems as a Tool to assist the electricity distribution Networks planning
spellingShingle Geographical information systems as a Tool to assist the electricity distribution Networks planning
Planificación del Sistema de Distribución
Sistemas de Información Geográfica
Geo procesamiento
Análisis Espacial
Características Socioeconómicas
sistemas de distribución de energia eléctrica
title_short Geographical information systems as a Tool to assist the electricity distribution Networks planning
title_full Geographical information systems as a Tool to assist the electricity distribution Networks planning
title_fullStr Geographical information systems as a Tool to assist the electricity distribution Networks planning
title_full_unstemmed Geographical information systems as a Tool to assist the electricity distribution Networks planning
title_sort Geographical information systems as a Tool to assist the electricity distribution Networks planning
dc.creator.fl_str_mv Mejia Alzate, Mario Andres
Melo Trujillo, Joel David
Padilha Feltrin, Antonio
Sánchez Zuleta, Carmen Cecilia
Fernández Gutiérrez, Juan Pablo
dc.contributor.author.spa.fl_str_mv Mejia Alzate, Mario Andres
Melo Trujillo, Joel David
Padilha Feltrin, Antonio
Sánchez Zuleta, Carmen Cecilia
Fernández Gutiérrez, Juan Pablo
dc.subject.spa.fl_str_mv Planificación del Sistema de Distribución
Sistemas de Información Geográfica
Geo procesamiento
Análisis Espacial
Características Socioeconómicas
sistemas de distribución de energia eléctrica
topic Planificación del Sistema de Distribución
Sistemas de Información Geográfica
Geo procesamiento
Análisis Espacial
Características Socioeconómicas
sistemas de distribución de energia eléctrica
description ABSTRACT. In recent years, the population growth in urban areas of Latin American cities has resulted in an increase in demand for electricity in a dispersed manner, bringing challenges to the planning of distribution systems to supply this demand. In addition, incentives for the installation of distributed generation make it necessary to carry out analyzes with a spatial perspective to determine the places of impact in the electricity distribution networks. Geographic information systems are computational tools that allow the processing of data with geographic reference. These systems can collaborate in the visualization of the socioeconomic characteristics and the variables distributed in the zone of study, being able to provide information to the distribution planners. This work shows computational tools that will help distribution utilities, using techniques available in geographic information systems to characterize the local factors in concession zone of the distribution utilities.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2018-04-30 00:00:00
2022-06-17T20:19:32Z
dc.date.available.none.fl_str_mv 2018-04-30 00:00:00
2022-06-17T20:19:32Z
dc.date.issued.none.fl_str_mv 2018-04-30
dc.type.spa.fl_str_mv Artículo de revista
dc.type.eng.fl_str_mv Journal article
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dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.references.eng.fl_str_mv Bibliographic references
• Books
DIGGLE, P. and RIBEIRO, P. J. Model – based Geostatistics. Springer Series in Statistics. Editorial Springer., New York, 2007.
FOTHERINGHAM, A. S.; BRUNSDON, C. and CHARLTON M. Geographically Weighted Regression. The analysis of spatially varying relationships. Editorial WILEY, England, 2002.
GONEN, T. Electric power distribution system engineering. Boca Raton: CRC Press, 2014.
KAGAN, N. Redes elétricas inteligentes no Brasil: análise de custos e benefícios de um plano nacional de implantação. Rio de Janeiro: Synergia Editora, 2013. 260 pag.
GUTIERREZ, J. and GOULD, M. SIG: Sistemas de Información Geográfica. Editorial Síntesis S.A., Madrid, 1994.
CAMARA, G. E. A. Mapping Social Exclusion/Inclusion in Developing Countries: social Dynamics of São Paulo in th 1990s. In: GOODCHILD, M. F.; JANELLE, D. G. Spatially integrated social science. New York: : Oxford University Press, 2004. Cap. 11, p. 223-237.
MIRANDA, J. I. Fundamentos de sistemas de informações geográficas. 4a. ed. [S.l.]: [s.n.], 2015.
SILVA, A. D. B. Sistemas de informações geo-referenciadas: conceitos e fundamentos. [S.l.]: [s.n.], 2003.
SILVA LORA, E. E. e ADDAD, J. Geração distribuída: aspectos tecnológicos, ambientais e institucionais. Rio de Janeiro: Inter ciência, 2006.
• Dissertations
MEJIA ALZATE, M. Previsão Espaço-temporal de demanda incluindo alterações nos hábitos de consumidores residenciais. Disertação de Mestrado. Universidade Estadual Paulista. Faculdade de Engenharia de Ilha Solteira. Ilha Solteira, p. 78. 2017. Disponível em: <http://hdl.handle.net/11449/148538>
VILLAVICENCIO GASTELU, J. Análise Espacial do potencial fotovoltaico em telhados de residência usando modelagem hierárquica bayesiana. Disertação de Mestrado. Universidade Estadual Paulista. Faculdade de Engenharia de Ilha Solteira. Ilha Solteira, p. 101. 2016. Disponível em: <http://hdl.handle.net/11449/137801>.
• Articles
ACEVEDO, I. y VELÁSQUEZ, E. “Algunos conceptos de la econometría espacial y el análisis exploratorio de datos espaciales”. Ecos de Economía. Num 27. Medellín, Colombia 2008. Disponible en: <http://publicaciones.eafit.edu.co/index.php/ecos-economia/article/viewFile/705/627>
ARANEDA E. “Uso de Sistemas de Información Geográficos y análisis espacial en arqueología: Proyecciones y limitaciones”. Estudios Atacameños. Num. 22, pag. 59-75 Santiago, Chile 2002. Disponible en: < http://dx.doi.org/10.4067/S0718-10432002002200004 >
BUZAI, G. D. “Modelos de localización-asignación aplicados a servicios públicos urbanos: análisis espacial de Centros de Atención Primaria de Salud (caps) en la ciudad de Luján, Argentina”. Cuadernos de geografía: revista colombiana de geografía. Vol. 20, Num. 2, pag. 111 – 123 Bogotá, 2011.
COMBER, A. J.; BRUNSDON, C.; HARDY, J. and RADBURN, R. “Using a GIS–based network analysis and optimisation routines to evaluate service provision: a case study of the UK”. Post Office Applied Spatial Analysis and Policy. Vol. 2, Num. 1, pag. 47 – 64, 2009.
COMBER, A.; DICKIE, J.; JARVIS, C.; PHILLIPS, M. and TANSEY, K. “Locating bioenergy facilities using a modified GIS-based location-allocation-algorithm: considering the spatial distribution of resource supply, unpublishing submitted paper”. Department of Geography, University of Leicester, Leicester, LE1 7RH, UK (2015) Availavel in: <https://lra.le.ac.uk/bitstream/2381/32346/4/Comber_AE_submission_March_2015.pdf.>
COMBER, A. J.; SASAKI, S.; SUZUKI, H. and BRUNSDON, C. “A modified grouping genetic algorithm to select ambulance site locations”. International Journal of Geographical Information Science, Vol. 25, Num. 5, pag. 807 – 823, 2011.
CHURCH, R. and REVELLE, C. “The maximal covering location problem”. Papers in Regional Science, Vol. 32, Num. 1, pag. 101 – 118, 1974.
HAKIMI, S. “Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph”. Operations Research, Vol. 12, pag. 450 – 459, 1964.
HAMMONS, T. J. “Renewable energy alternatives for developed countries”. IEEE Transactions on Energy Conversion, Piscataway, Vol. 15, Num. 4, pag. 481-493, 2000.
HO, C. and K. C. “Impact of grid-connected residential PV systems on the Malaysia low voltage distribution network”. IEEE conference, Power engineering and optimization, Langkawi Island, Malaysia. pag. 670 – 675. , 2013.
LEOU, R. C.; TENG, J. H. and SU, C. L. “Modelling and verifying the load behaviour of electric vehicle charging stations based on field measurements”. IET Generation, Transmission & Distribution , Vol. 9, Num. 11, pag. 1112 - 1119, August 2015.
MEJIA, M. A.; MELO, J. D.; ZAMBRANO-ASANZA, S. e FELTRIN, A. P. “Regressão Ponderada Geograficamente para estimar a distribuição espacial do potencial de mercado de um eletrodoméstico com alto consumo de energia elétrica”. Congresso Brasilero de Automatica [S.l.]: CBA. 2016.
MELO, J. D.; ZAMBRANO-ASANZA, S. and PADILHA-FELTRIN, A. “A local search algorithm to allocate loads predicted by spatial load forecasting studies”. Electric Power System Research, Vol. 146, pag. 206–217, May 2017.
OWEN, S. H., AND DASKIN, M. S. “Strategic facility location: A review”. European Journal of Operational Research, Vol. 111. Num. 3, pag. 423 - 447, 1998.
QUIROS-TORTOS, J.; VALVERDE, G.; ARGÜELLO, A. and OCHOA, L. N. “Geo-Information Is Power: Using Geographical Information Systems to Assess Rooftop Photovoltaics in Costa Rica”. IEEE Power and Energy Magazine, Vol. 15, Num. 2, pag. 48 - 56, March 2017. Available in: https://www.researchgate.net/publication/314200428_Geo-Information_Is_Power_Using_Geographical_Information_Systems_to_Assess_Rooftop_Photovoltaics_in_Costa_Rica
REVELLE, C. S. and SWAIN, R. W. “Central facilities location”. Geographic Analysis, Vol. 2, pag. 30 - 42, 1970. RUBIO BARROSO, A. y GUTIERREZ, J. “Los Sistemas de Información Geográficos: Origen y perspectivas”. Revista General de Información y Documentación, Vol. 7, Num. 1. Servicio de Publicaciones Universidad Complutense. Madrid. 1997 Disponible en: http://revistas.ucm.es/index.php/RGID/article/viewFile/RGID9797120093A/10990
SASAKI, S.; COMBER, A. J.; SUZUKI, H. and BRUNSDON, C. “Using genetic algorithms to optimise current and future health planning - the example of ambulance locations”. International Journal of Health Geographics, Vol. 9, pag. 4 - 12, 2010. Availavel in < doi:10.1186/1476-072X-9-4>
SASAKI, S.; IGARASHI, K.; FUJINO, Y.; COMBER, A. J.; BRUNSDON, C.; MULEYA, C. M. and SUZUKI, H. “The impact of community-based outreach immunization services on immunization coverage with GIS network accessibility analysis in peri-urban areas, Zambia”. Journal of Epidemiology and Community Health, Vol 65, pag. 1171-1178, 2011. Availavel in <doi:10.1136/jech.2009.104190>
SHU, J. A new method for spatial power network planning in complicated environments. IEEE Transactions on Power Systems , Vol. 27, Num. 1, pag. 381-389, Feb. 2012.
VILLAVICENCIO, J.; MELO, J. D. and FELTRIN, A. P. “Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator”. IEEE PES Innovation Smart Grid Technologies Latin America – ISGT LATAM. [S.l.]: IEEE. 2015.
WATSON, J. D. “Impact of solar photovoltaics on the low-voltage distribution network in New Zealand”. IET Generation, Transmission & Distribution, Stevenage, Vol. 10, Num. 1, pag. 1-9, 2016.
WEI, W. “Expansion Planning of Urban Electrified Transportation Networks: A Mixed-Integer Convex Programming Approach”. IEEE Transactions on Transportation Electrification, Vol. 3, Num. 1, pag. 210 - 224, March 2017.
ZAHEDI, A. “Australian renewable energy progress”. Renewable and Sustainable Energy Reviews, Oxford, Vol. 14, Num. 8, pag. 2208–2213, 2010.
• Websites
RENEWABLES 2015 GLOBAL STATUS REPORT. Renewable energy policy network for the 21th century (REN21), 2015. Disponível em : <http://www.nrel.gov/docs/fy08osti/42306.pdf>. Acesso em: 10 jun. 2017.
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dc.relation.citationedition.spa.fl_str_mv Núm. 29 , Año 2018
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dc.relation.citationstartpage.none.fl_str_mv 71
dc.relation.citationvolume.spa.fl_str_mv 15
dc.relation.ispartofjournal.spa.fl_str_mv Revista EIA
dc.rights.eng.fl_str_mv Revista EIA - 2018
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spelling Mejia Alzate, Mario Andres27e98e8724488a0de045b613a168878d300Melo Trujillo, Joel David69fd0a67107e6680f01e9a4ada1eddde300Padilha Feltrin, Antonio3d959ba24eb2d987520b00f3093ab94a300Sánchez Zuleta, Carmen Cecilia38bd3f4b9ed6c87f0302fa6bdbbb221b300Fernández Gutiérrez, Juan Pablo2f78cbae04d3177bfea46b1b99cd876a3002018-04-30 00:00:002022-06-17T20:19:32Z2018-04-30 00:00:002022-06-17T20:19:32Z2018-04-301794-1237https://repository.eia.edu.co/handle/11190/500910.24050/reia.v15i29.11382463-0950https://doi.org/10.24050/reia.v15i29.1138ABSTRACT. In recent years, the population growth in urban areas of Latin American cities has resulted in an increase in demand for electricity in a dispersed manner, bringing challenges to the planning of distribution systems to supply this demand. In addition, incentives for the installation of distributed generation make it necessary to carry out analyzes with a spatial perspective to determine the places of impact in the electricity distribution networks. Geographic information systems are computational tools that allow the processing of data with geographic reference. These systems can collaborate in the visualization of the socioeconomic characteristics and the variables distributed in the zone of study, being able to provide information to the distribution planners. This work shows computational tools that will help distribution utilities, using techniques available in geographic information systems to characterize the local factors in concession zone of the distribution utilities.In recent years, the population growth in urban areas of Latin American cities has resulted in an increase in demand for electricity in a dispersed manner, bringing challenges to the planning of distribution systems to supply this demand. In addition, incentives for the installation of distributed generation make it necessary to carry out analyzes with a spatial perspective to determine the places of impact in the electricity distribution networks. Geographic information systems are computational tools that allow the processing of data with geographic reference. These systems can collaborate in the visualization of the socioeconomic characteristics and the variables distributed in the zone of study, being able to provide information to the distribution planners. This work shows computational tools that will help distribution utilities, using techniques available in geographic information systems to characterize the local factors in concession zone of the distribution utilities.application/pdfengFondo Editorial EIA - Universidad EIARevista EIA - 2018https://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://revistas.eia.edu.co/index.php/reveia/article/view/1138Planificación del Sistema de DistribuciónSistemas de Información GeográficaGeo procesamientoAnálisis EspacialCaracterísticas Socioeconómicassistemas de distribución de energia eléctricaGeographical information systems as a Tool to assist the electricity distribution Networks planningGeographical Information Systems as a Tool to Assist the Electricity Distribution Networks PlanningArtículo de revistaJournal articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/redcol/resource_type/ARTREFhttp://purl.org/coar/version/c_970fb48d4fbd8a85Bibliographic references• BooksDIGGLE, P. and RIBEIRO, P. J. Model – based Geostatistics. Springer Series in Statistics. Editorial Springer., New York, 2007.FOTHERINGHAM, A. S.; BRUNSDON, C. and CHARLTON M. Geographically Weighted Regression. The analysis of spatially varying relationships. Editorial WILEY, England, 2002.GONEN, T. Electric power distribution system engineering. Boca Raton: CRC Press, 2014.KAGAN, N. Redes elétricas inteligentes no Brasil: análise de custos e benefícios de um plano nacional de implantação. Rio de Janeiro: Synergia Editora, 2013. 260 pag.GUTIERREZ, J. and GOULD, M. SIG: Sistemas de Información Geográfica. Editorial Síntesis S.A., Madrid, 1994.CAMARA, G. E. A. Mapping Social Exclusion/Inclusion in Developing Countries: social Dynamics of São Paulo in th 1990s. In: GOODCHILD, M. F.; JANELLE, D. G. Spatially integrated social science. New York: : Oxford University Press, 2004. Cap. 11, p. 223-237.MIRANDA, J. I. Fundamentos de sistemas de informações geográficas. 4a. ed. [S.l.]: [s.n.], 2015.SILVA, A. D. B. Sistemas de informações geo-referenciadas: conceitos e fundamentos. [S.l.]: [s.n.], 2003.SILVA LORA, E. E. e ADDAD, J. Geração distribuída: aspectos tecnológicos, ambientais e institucionais. Rio de Janeiro: Inter ciência, 2006.• DissertationsMEJIA ALZATE, M. Previsão Espaço-temporal de demanda incluindo alterações nos hábitos de consumidores residenciais. Disertação de Mestrado. Universidade Estadual Paulista. Faculdade de Engenharia de Ilha Solteira. Ilha Solteira, p. 78. 2017. Disponível em: <http://hdl.handle.net/11449/148538>VILLAVICENCIO GASTELU, J. Análise Espacial do potencial fotovoltaico em telhados de residência usando modelagem hierárquica bayesiana. Disertação de Mestrado. Universidade Estadual Paulista. Faculdade de Engenharia de Ilha Solteira. Ilha Solteira, p. 101. 2016. Disponível em: <http://hdl.handle.net/11449/137801>.• ArticlesACEVEDO, I. y VELÁSQUEZ, E. “Algunos conceptos de la econometría espacial y el análisis exploratorio de datos espaciales”. Ecos de Economía. Num 27. Medellín, Colombia 2008. Disponible en: <http://publicaciones.eafit.edu.co/index.php/ecos-economia/article/viewFile/705/627>ARANEDA E. “Uso de Sistemas de Información Geográficos y análisis espacial en arqueología: Proyecciones y limitaciones”. Estudios Atacameños. Num. 22, pag. 59-75 Santiago, Chile 2002. Disponible en: < http://dx.doi.org/10.4067/S0718-10432002002200004 >BUZAI, G. D. “Modelos de localización-asignación aplicados a servicios públicos urbanos: análisis espacial de Centros de Atención Primaria de Salud (caps) en la ciudad de Luján, Argentina”. Cuadernos de geografía: revista colombiana de geografía. Vol. 20, Num. 2, pag. 111 – 123 Bogotá, 2011.COMBER, A. J.; BRUNSDON, C.; HARDY, J. and RADBURN, R. “Using a GIS–based network analysis and optimisation routines to evaluate service provision: a case study of the UK”. Post Office Applied Spatial Analysis and Policy. Vol. 2, Num. 1, pag. 47 – 64, 2009.COMBER, A.; DICKIE, J.; JARVIS, C.; PHILLIPS, M. and TANSEY, K. “Locating bioenergy facilities using a modified GIS-based location-allocation-algorithm: considering the spatial distribution of resource supply, unpublishing submitted paper”. Department of Geography, University of Leicester, Leicester, LE1 7RH, UK (2015) Availavel in: <https://lra.le.ac.uk/bitstream/2381/32346/4/Comber_AE_submission_March_2015.pdf.>COMBER, A. J.; SASAKI, S.; SUZUKI, H. and BRUNSDON, C. “A modified grouping genetic algorithm to select ambulance site locations”. International Journal of Geographical Information Science, Vol. 25, Num. 5, pag. 807 – 823, 2011.CHURCH, R. and REVELLE, C. “The maximal covering location problem”. Papers in Regional Science, Vol. 32, Num. 1, pag. 101 – 118, 1974.HAKIMI, S. “Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph”. Operations Research, Vol. 12, pag. 450 – 459, 1964.HAMMONS, T. J. “Renewable energy alternatives for developed countries”. IEEE Transactions on Energy Conversion, Piscataway, Vol. 15, Num. 4, pag. 481-493, 2000.HO, C. and K. C. “Impact of grid-connected residential PV systems on the Malaysia low voltage distribution network”. IEEE conference, Power engineering and optimization, Langkawi Island, Malaysia. pag. 670 – 675. , 2013.LEOU, R. C.; TENG, J. H. and SU, C. L. “Modelling and verifying the load behaviour of electric vehicle charging stations based on field measurements”. IET Generation, Transmission & Distribution , Vol. 9, Num. 11, pag. 1112 - 1119, August 2015.MEJIA, M. A.; MELO, J. D.; ZAMBRANO-ASANZA, S. e FELTRIN, A. P. “Regressão Ponderada Geograficamente para estimar a distribuição espacial do potencial de mercado de um eletrodoméstico com alto consumo de energia elétrica”. Congresso Brasilero de Automatica [S.l.]: CBA. 2016.MELO, J. D.; ZAMBRANO-ASANZA, S. and PADILHA-FELTRIN, A. “A local search algorithm to allocate loads predicted by spatial load forecasting studies”. Electric Power System Research, Vol. 146, pag. 206–217, May 2017.OWEN, S. H., AND DASKIN, M. S. “Strategic facility location: A review”. European Journal of Operational Research, Vol. 111. Num. 3, pag. 423 - 447, 1998.QUIROS-TORTOS, J.; VALVERDE, G.; ARGÜELLO, A. and OCHOA, L. N. “Geo-Information Is Power: Using Geographical Information Systems to Assess Rooftop Photovoltaics in Costa Rica”. IEEE Power and Energy Magazine, Vol. 15, Num. 2, pag. 48 - 56, March 2017. Available in: https://www.researchgate.net/publication/314200428_Geo-Information_Is_Power_Using_Geographical_Information_Systems_to_Assess_Rooftop_Photovoltaics_in_Costa_RicaREVELLE, C. S. and SWAIN, R. W. “Central facilities location”. Geographic Analysis, Vol. 2, pag. 30 - 42, 1970. RUBIO BARROSO, A. y GUTIERREZ, J. “Los Sistemas de Información Geográficos: Origen y perspectivas”. Revista General de Información y Documentación, Vol. 7, Num. 1. Servicio de Publicaciones Universidad Complutense. Madrid. 1997 Disponible en: http://revistas.ucm.es/index.php/RGID/article/viewFile/RGID9797120093A/10990SASAKI, S.; COMBER, A. J.; SUZUKI, H. and BRUNSDON, C. “Using genetic algorithms to optimise current and future health planning - the example of ambulance locations”. International Journal of Health Geographics, Vol. 9, pag. 4 - 12, 2010. Availavel in < doi:10.1186/1476-072X-9-4>SASAKI, S.; IGARASHI, K.; FUJINO, Y.; COMBER, A. J.; BRUNSDON, C.; MULEYA, C. M. and SUZUKI, H. “The impact of community-based outreach immunization services on immunization coverage with GIS network accessibility analysis in peri-urban areas, Zambia”. Journal of Epidemiology and Community Health, Vol 65, pag. 1171-1178, 2011. Availavel in <doi:10.1136/jech.2009.104190>SHU, J. A new method for spatial power network planning in complicated environments. 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Disponível em : <http://www.nrel.gov/docs/fy08osti/42306.pdf>. Acesso em: 10 jun. 2017.https://revistas.eia.edu.co/index.php/reveia/article/download/1138/1177Núm. 29 , Año 201885297115Revista EIAPublicationOREORE.xmltext/xml2803https://repository.eia.edu.co/bitstreams/dbdaeb77-a3af-4ee1-ac6c-29375dc9f20f/download046748ebc4d861daad41cafa08549bfaMD5111190/5009oai:repository.eia.edu.co:11190/50092023-07-25 17:16:17.133https://creativecommons.org/licenses/by-nc-sa/4.0/Revista EIA - 2018metadata.onlyhttps://repository.eia.edu.coRepositorio Institucional Universidad EIAbdigital@metabiblioteca.com

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