Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente
ilustraciones
- Autores:
-
Téllez Gutiérrez, Sandra Milena
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2022
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/83287
- Palabra clave:
- Ingeniería Eléctrica
Gestión de la Demanda
Abastecimiento de energía
Consumo de energía
Energy supply
Energy consumption
Gestión de la Demanda
Modelos cuantitativos
Respuesta de la Demanda
Smart Grids
Demand-side management
Mathematical models
Consumer behavior
Energy management
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| dc.title.translated.eng.fl_str_mv |
Demand-side management strategies approach from the active end-user in an electric smart grid |
| title |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| spellingShingle |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente Ingeniería Eléctrica Gestión de la Demanda Abastecimiento de energía Consumo de energía Energy supply Energy consumption Gestión de la Demanda Modelos cuantitativos Respuesta de la Demanda Smart Grids Demand-side management Mathematical models Consumer behavior Energy management |
| title_short |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| title_full |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| title_fullStr |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| title_full_unstemmed |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| title_sort |
Planteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligente |
| dc.creator.fl_str_mv |
Téllez Gutiérrez, Sandra Milena |
| dc.contributor.advisor.none.fl_str_mv |
Duarte Velasco, Oscar Germán |
| dc.contributor.author.none.fl_str_mv |
Téllez Gutiérrez, Sandra Milena |
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Grisec |
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0000-0002-8303-3611 |
| dc.subject.ddc.spa.fl_str_mv |
Ingeniería Eléctrica Gestión de la Demanda |
| topic |
Ingeniería Eléctrica Gestión de la Demanda Abastecimiento de energía Consumo de energía Energy supply Energy consumption Gestión de la Demanda Modelos cuantitativos Respuesta de la Demanda Smart Grids Demand-side management Mathematical models Consumer behavior Energy management |
| dc.subject.lemb.spa.fl_str_mv |
Abastecimiento de energía Consumo de energía |
| dc.subject.lemb.eng.fl_str_mv |
Energy supply Energy consumption |
| dc.subject.proposal.spa.fl_str_mv |
Gestión de la Demanda Modelos cuantitativos Respuesta de la Demanda |
| dc.subject.proposal.eng.fl_str_mv |
Smart Grids Demand-side management Mathematical models Consumer behavior Energy management |
| description |
ilustraciones |
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2022 |
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2022-09-22 |
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2023-02-03T16:49:02Z |
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2023-02-03T16:49:02Z |
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Trabajo de grado - Doctorado |
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Universidad Nacional de Colombia |
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M. Alizadeh, X. Li, Z. Wang, A. Scaglione, and R. Melton, “Demand-Side Management in the Smart Grid,” IEEE Signal processing Magazine, no. September, pp. 55–67, 2012. M. A. C. Moreno, “Gesti´on activa de la demanda de energ´ıa el´ectrica,” PhD thesis, Universidad Carlos III de MAdrid, 2010, p. 102. European Comission, European Smart Grids Technology Platform. Brussels, 2006, p. 44, isbn: 9279014145. J. Xia and Y. Wang, “Secure Key Distribution for the Smart Grid,” IEEE Transactions on Smart Grid, vol. 3, no. 3, pp. 1437–1443, Sep. 2012, issn: 1949-3053. doi: 10.1109/TSG.2012.2199141. [Online]. Available: http:// ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6205351 R. Cespedes, “A reference model for the electrical energy system based on Smart Grids,” 2012 Sixth IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), pp. 1–6, Sep. 2012. doi: 10.1109/TDCLA . 2012 . 6319068. [Online]. Available: http : / / ieeexplore . ieee . org / lpdocs/epic03/wrapper.htm?arnumber=6319068. S. Tellez, D. Alvarez, W. Montano, C. Vargas, R. Cespedes, E. Parra, and J. Rosero, “National Laboratory of Smart Grids ( LAB + i ) at the National University of Colombia-Bogota Campus,” in IEEE T&DLA Transmission and Distribution Conference, 2014, isbn: 9781479962518 Federal Energy Regulatory Commission, “Assessment of Demand Response and Advanced Metering - Staff Report,” Tech. Rep., 2006 C. Gellings, “The concept of demand-side management for electric utilities,” Proceedings of the IEEE, vol. 73, no. 10, pp. 1468–1470, 1985, issn: 0018-9219. doi: 10.1109/PROC.1985.13318. C. Gu, L. Liu, T. Zhang, and Y. Zheng, “Demand response model and impact studies based on bidirectional interactive of information and electrical energy,” 2012 China International Conference on Electricity Distribution, no. Ciced, pp. 1–6, Sep. 2012. doi: 10.1109/CICED.2012.6508575. C. Grajales and L. Figueroa, “Programas de respuesta en demanda y su posible impacto en el sistema el´ectrico colombiano,” PhD thesis, Universidad Tecnologica de Pereira, 2012, p. 82. International Energy Agency (IEA) and Organization for Economic Cooperation and Development (OECD), “The Power to choose: Demand Response in Liberalised Electricicty Markets,” Paris - France, Tech. Rep., 2003. North American Electric Reliability Corporation (NERC), “Demand Response Availability Data Systems Definitions,” Atlanta, Tech. Rep. March, 2014 P. Palensky and D. Dietrich, “Demand Side Management : Demand Response , Intelligent Energy Systems , and Smart Loads,” IEEE Transaction on Industrial Informatics, vol. 7, no. 3, pp. 381–388, 2011. W. Gellings, “Evolving practice of demand-side management,” 2016 Modern Power Systems and Clean Energy, no. 5, pp. 1–9, 2016. doi: 10.1007/s40565- 016-0252-1. A. F. Meyabadi and M. Deihimi, “A review of demand-side management: Reconsidering theoretical framework,” Renewable and Sustainable Energy Reviews, vol. 80, pp. 367–379, 2017, issn: 1364-0321 B. P. Esther and K. S. Kumar, “A survey on residential Demand Side Management architecture, approaches, optimization models and methods,” Renewable and Sustainable Energy Reviews, vol. 59, pp. 342–351, 2016, issn: 1364-0321 A. Shewale, A. Mokhade, N. Funde, and N. D. Bokde, “An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem,” Energies, vol. 13, no. 16, 2020, issn: 1996-1073. A. Brezavˇsˇcek and D. Kofjac, “The use of quantitative methods for electricity demand forecasting,” in 32. mednarodna konferenca o razvoju organizacijskih znanosti PAMETNA ORGANIZACIJA Talenti., Portoroˇz, Slovenija, 2013 Unidad de Planeacion Minero Energetica (UPME), C. Garc´ıa, and M. William, Modelo para la proyeccion de demanda de energıa electrica en colombia, Bogota, Colombia, 2014 IEA DSM, “IEA DSM TASK 25: Business models for a more effective market uptake of EE energy services for SMEs and communities,” Tech. Rep., 2014, p. 34. a. Mahmood, M. Ullah, S. Razzaq, a. Basit, U. Mustafa, M. Naeem, and N. Javaid, “A New Scheme for Demand Side Management in Future Smart Grid Networks,” Procedia Computer Science, vol. 32, pp. 477–484, 2014, issn: 18770509 J. S. Vardakas, N. Zorba, and C. V. Verikoukis, “A Survey on Demand Response in Smart Grids: Pricing Methods and Optimization Algorithms,” IEEE Transactions on Industrial Informatics, vol. 11, no. 3, p. 1, 2015, issn: 1551-3203. doi: 10.1109/TII.2015.2414719. Marcela Jim´enez Castrill´on, “Estudio de la viabilidad de implementaci´on de tecnolog´ıas Smart Grids en el mercado el´ectrico colombiano,” PhD thesis, Universidad Pontificia Bolivariana, 2013, p. 118. M. A. L´opez, S. D. Torre, S. Mart´ın, and J. A. Aguado, “Demand-side management in smart grid operation considering electric vehicles load shifting and vehicle-to-grid support,” vol. 64, pp. 689–698, 2014. doi: 10.1016/j.ijepes. 2014.07.065 N. G. Paterakis, O. Erdin¸c, and J. P. Catal˜ao, “An overview of Demand Response: Key-elements and international experience,” Renewable and Sustainable Energy Reviews, vol. 69, no. December 2016, pp. 871–891, 2017, issn: 18790690. H. J. Jabir, J. Teh, D. Ishak, and H. Abunima, “Impact of demand-side management on the reliability of generation systems,” Energies, vol. 11, no. 8, 2018, issn: 1996-1073. doi: 10.3390/en11082155. [Online]. S. Nolan and M. O’Malley, “Challenges and barriers to demand response deployment and evaluation,” Applied Energy, vol. 152, pp. 1–10, 2015, issn: 03062619. doi: 10.1016/j.apenergy.2015.04.083 P. Bradley, M. Leach, and J. Torriti, “A review of the costs and benefits of demand response for electricity in the UK,” Energy Policy, vol. 52, pp. 312– 327, 2013, Grupo T´ecnico Proyecto BID, “Smart Grids Colombia Vision 2030 Parte II - Mapa de Ruta: Construcci`on y Resultados (Componente I),” Bogot´a-Colombia, Tech. Rep., 2016, p. 183. S. M. T´ellez Guti´errez, J. Rosero Garc´ıa, and R. C´espedes Gandarillas, “Sistemas de medici´on avanzada en Colombia : beneficios , retos y oportunidades Advanced metering infrastructure in Colombia : benefits , challenges and opportunities,” Ingenier´ıa y desarrollo. Universidad del Norte, vol. Vol. 36 n. No. Julio-diciembre, pp. 469–488, 2018. doi: ISSN:0122-3461 L. L. Bernal Mart´ınez, “Marco Conceptual de la Gobernanza de Datos en el Dominio de las Redes Inteligentes en Colombia,” PhD thesis, Universidad Nacional de Colombia, 2018, p. 288. A. Keyhani and B. Ramachandran, “Real-time simulation of demand side management and vehicle to grid power flow in a smart distribution grid,” in 2017 IEEE International Conference on Electro Information Technology (EIT), 2017, pp. 1–5. doi: 10.1109/EIT.2017.8053426. H. Sui, Y. Sun, and W.-J. Lee, “A demand side management model based on advanced metering infrastructure,” in 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011, pp. 1586–1589. doi: 10.1109/DRPT.2011.5994150. O. G. Duarte, “T´ecnicas difusas en la evaluaci´on de impacto ambiental,” PhD thesis, Universidad de Granada, 2000. M. Delgado, O. G. Duarte, and I. Requena, “An arithmetic approach for the computing with words paradigm,” International journal of intelligent systems, vol. 21, no. 2, pp. 121–142, 2006. O. G. Duarte and S. T´ellez, “A family of owa operators based on faulhaber’s formulas,” arXiv preprint arXiv:1801.10545, 2018. M. Delgado, M. Vila, and W. Voxman, “On a canonical representation of fuzzy numbers,” no. 93, pp. 205–216, 1988. I. Requena, A.Blanco, and M. Delgado, “A decision personal index of fuzzy numbers based on neural networks,” vol. 73, no. 2, pp. 185–199, 1995. |
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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Duarte Velasco, Oscar Germán1300d3b1a51c257ef0951e93324c6e78Téllez Gutiérrez, Sandra Milena633cb58572297d4e64758efcbbfd00aaGrisec0000-0002-8303-36112023-02-03T16:49:02Z2023-02-03T16:49:02Z2022-09-22https://repositorio.unal.edu.co/handle/unal/83287Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesEl principal objetivo de la cadena de energía eléctrica y todos sus sistemas asociados es atender oportuna y eficientemente la demanda de los usuarios, cumpliendo con los requerimientos de calidad y confiabilidad del servicio. Factores como los económicos, sociales y meteorológicos influyen sobre la demanda de energía eléctrica. Puede ser de interés conocer la demanda total que demandará un sistema global o estudiar el comportamiento de la demanda de energía desde los puntos de consumo. Son los usuarios finales de energía quienes determinan, de acuerdo a sus patrones de consumo y las características de su contexto local, la cantidad de energía que demandarán en cada período de tiempo. Esto quiere decir que los grandes generadores del sistema no pueden controlar la demanda de forma directa; por esta razón es necesario entender el comportamiento de la demanda y evaluar estrategias indirectas de para influenciarla. Los patrones de consumo tienen una alta diversidad y pueden ser más estables en unos usuarios que en otros, existen grupos de usuarios que presentan regularidad en la cantidad de energía y los intervalos de tiempo en que la requieren durante el día. También pueden encontrarse grupos de usuarios con patrones de consumo similares debido al uso final que le dan a la energía consumida, este hecho da origen a múltiples estudios de caracterización y predicción de la demanda. Tradicionalmente el sistema de potencia eléctrico ha necesitado adecuarse a la demanda de los usuarios, esto puede interpretarse como una respuesta del sistema a la demanda. Por otro lado, ha existido un interés para modificar los patrones de consumo de los usuarios a través de planes y estímulos se buscan obtener una respuesta de la demanda de los usuarios. Aquí se involucran las nuevas tecnologías como las smart grids. Esta tesis identifica el impacto de las características de los usuarios activos de energía eléctrica en la formulación de una estrategia de implementación de programas locales de Gestión de la Demanda de Energía Eléctrica aplicable a contextos Colombianos. En el Capitulo 1 se introduce el tema y planteamiento general de la investigación, en el capítulo 2 se presenta un marco teórico construido a partir del estado del arte y se propone como complemento un nuevo marco teórico que incluye conceptos que se desarrollan en esta tesis. El capítulo 3 desarrolla un modelo cualitativo del a gestión de la demanda basado en análisis PESTAL y presenta un análisis de influencias que fueron validados por expertos mediante Análisis Jerárquico. En el capítulo 4 se presenta el modelo cuantitativo para estimar las modificaciones en los patrones de consumo ante técnicas clásicas de respuesta de la demanda como los programas de precios variables en el tiempo, considerando adicionalmente nuevos factores como la cultura energética. El capítulo 5 incluye el desarrollo de software en Modelica que permitió implementar el modelo. En el capítulo 6 se presentan los ejercicios de simulación desarrollados con el modelo junto con los resultados encontrados. El capítulo 7 presenta la validación de los resultados realizados por expertos en el área y el capítulo 8 expone las conclusiones y recomendaciones de la investigación. (Texto tomado de la fuente)Final energy consumers themselves determine the quantity of energy that will be consumed in each period of time, according to their electricity consumption patterns and the particularities of their local context. This implies that large power generators in the system are not able to directly control the demand; therefore, it is necessary to understand its behavior and to evaluate strategies to indirectly control it. Electricity consumption patterns are highly diverse. Some patterns tend to be more stable than others depending on the user behavior, that is, there are users that have a regular behavior in terms of the quantity of consumed electricity and the time intervals during the day when the consumption occurs. Also, there are groups of users that have similar consumption patterns due to the given end use of the electricity consumed, this fact gives rise to a variety of studies dealing with the characterization and forecasting of demand . Traditionally, the electric power system has needed to be tailored to users’ demand, this can be interpreted as a system's response to the demand. Conversely, there has been an interest to modify user consumption patterns through plans and incentives that seek a user’s demand responsiveness. Worldwide, DSM has been studied from different perspectives , mainly the technical aspects of DR; each country or region has characteristics that need to be considered. The Colombian electricity sector has implemented DR programs, for example, the Apagar-Paga program that achieved savings of 500 GWh and 170 MW in one month. Also, the mechanisms Voluntary Disconnectable Demand (DVD) and DR in critical conditions registered availabilities of more than 171 MW and 76 MW, respectively. The diversity of criteria, requirements, and information needed to implement a DSM strategy is wide and depends on the local context. It is necessary to consider all aspects related to loading profile variations for each end-user. Given the limited experience in Colombia in the design and implementation of DSM strategies, it is necessary to create a model to conceptualize, implement and validate a model to determine load profile variations and other variables associated. This thesis identifies the impact of the characteristics of active energy end-users in the formulation of a strategy for the implementation of local programs of Demand-side management applicable to Colombian contexts. In Chapter 1, the topic and general approach of the investigation are introduced, in Chapter 2 presents a theoretical framework built from the state of the art and proposes as a complement, a new theoretical framework that includes concepts that are developed in this thesis. Chapter 3 develops a qualitative model of demand management based on PESTAL analysis and presents an analysis of influences that were validated by experts through Hierarchical Analysis. In chapter 4 the quantitative model to estimate the changes in consumption patterns before classical response techniques of the demand, as well as time-varying price programs, additionally considering new factors such as energy culture. Chapter 5 includes software development in Modelica that allowed the model to be implemented. In chapter 6 the exercises are presented. Simulations developed with the model together with the results found. Chapter 7 presents the validation of the results carried out by experts in the area, and chapter 8 presents the conclusions and recommendations of the investigation.DoctoradoDoctora en Ingeniería EléctricaGestión de la energíaSmart Gridsdsxxxv, 180 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Doctorado en Ingeniería - Ingeniería EléctricaFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede BogotáIngeniería EléctricaGestión de la DemandaAbastecimiento de energíaConsumo de energíaEnergy supplyEnergy consumptionGestión de la DemandaModelos cuantitativosRespuesta de la DemandaSmart GridsDemand-side managementMathematical modelsConsumer behaviorEnergy managementPlanteamiento de estrategias para la Gestión de la Demanda desde el usuario activo en una red eléctrica inteligenteDemand-side management strategies approach from the active end-user in an electric smart gridTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDColombiaM. Alizadeh, X. Li, Z. Wang, A. Scaglione, and R. Melton, “Demand-Side Management in the Smart Grid,” IEEE Signal processing Magazine, no. September, pp. 55–67, 2012.M. A. C. Moreno, “Gesti´on activa de la demanda de energ´ıa el´ectrica,” PhD thesis, Universidad Carlos III de MAdrid, 2010, p. 102.European Comission, European Smart Grids Technology Platform. Brussels, 2006, p. 44, isbn: 9279014145.J. Xia and Y. Wang, “Secure Key Distribution for the Smart Grid,” IEEE Transactions on Smart Grid, vol. 3, no. 3, pp. 1437–1443, Sep. 2012, issn: 1949-3053. doi: 10.1109/TSG.2012.2199141. [Online]. Available: http:// ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6205351R. Cespedes, “A reference model for the electrical energy system based on Smart Grids,” 2012 Sixth IEEE/PES Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), pp. 1–6, Sep. 2012. doi: 10.1109/TDCLA . 2012 . 6319068. [Online]. Available: http : / / ieeexplore . ieee . org / lpdocs/epic03/wrapper.htm?arnumber=6319068.S. Tellez, D. Alvarez, W. Montano, C. Vargas, R. Cespedes, E. Parra, and J. Rosero, “National Laboratory of Smart Grids ( LAB + i ) at the National University of Colombia-Bogota Campus,” in IEEE T&DLA Transmission and Distribution Conference, 2014, isbn: 9781479962518Federal Energy Regulatory Commission, “Assessment of Demand Response and Advanced Metering - Staff Report,” Tech. Rep., 2006C. Gellings, “The concept of demand-side management for electric utilities,” Proceedings of the IEEE, vol. 73, no. 10, pp. 1468–1470, 1985, issn: 0018-9219. doi: 10.1109/PROC.1985.13318.C. Gu, L. Liu, T. Zhang, and Y. Zheng, “Demand response model and impact studies based on bidirectional interactive of information and electrical energy,” 2012 China International Conference on Electricity Distribution, no. Ciced, pp. 1–6, Sep. 2012. doi: 10.1109/CICED.2012.6508575.C. Grajales and L. Figueroa, “Programas de respuesta en demanda y su posible impacto en el sistema el´ectrico colombiano,” PhD thesis, Universidad Tecnologica de Pereira, 2012, p. 82.International Energy Agency (IEA) and Organization for Economic Cooperation and Development (OECD), “The Power to choose: Demand Response in Liberalised Electricicty Markets,” Paris - France, Tech. Rep., 2003.North American Electric Reliability Corporation (NERC), “Demand Response Availability Data Systems Definitions,” Atlanta, Tech. Rep. March, 2014P. Palensky and D. Dietrich, “Demand Side Management : Demand Response , Intelligent Energy Systems , and Smart Loads,” IEEE Transaction on Industrial Informatics, vol. 7, no. 3, pp. 381–388, 2011.W. Gellings, “Evolving practice of demand-side management,” 2016 Modern Power Systems and Clean Energy, no. 5, pp. 1–9, 2016. doi: 10.1007/s40565- 016-0252-1.A. F. Meyabadi and M. Deihimi, “A review of demand-side management: Reconsidering theoretical framework,” Renewable and Sustainable Energy Reviews, vol. 80, pp. 367–379, 2017, issn: 1364-0321B. P. Esther and K. S. Kumar, “A survey on residential Demand Side Management architecture, approaches, optimization models and methods,” Renewable and Sustainable Energy Reviews, vol. 59, pp. 342–351, 2016, issn: 1364-0321A. Shewale, A. Mokhade, N. Funde, and N. D. Bokde, “An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem,” Energies, vol. 13, no. 16, 2020, issn: 1996-1073.A. Brezavˇsˇcek and D. Kofjac, “The use of quantitative methods for electricity demand forecasting,” in 32. mednarodna konferenca o razvoju organizacijskih znanosti PAMETNA ORGANIZACIJA Talenti., Portoroˇz, Slovenija, 2013Unidad de Planeacion Minero Energetica (UPME), C. Garc´ıa, and M. 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Delgado, “A decision personal index of fuzzy numbers based on neural networks,” vol. 73, no. 2, pp. 185–199, 1995.LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83287/3/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD53ORIGINAL52190361.2022.pdf52190361.2022.pdfTesis de Doctorado en Ingeniería Eléctricaapplication/pdf4659562https://repositorio.unal.edu.co/bitstream/unal/83287/4/52190361.2022.pdf12b54365f91a61dabf2059492887746cMD54THUMBNAIL52190361.2022.pdf.jpg52190361.2022.pdf.jpgGenerated Thumbnailimage/jpeg4561https://repositorio.unal.edu.co/bitstream/unal/83287/5/52190361.2022.pdf.jpga7562b45f3201e4046a90568c51f7eaaMD55unal/83287oai:repositorio.unal.edu.co:unal/832872023-08-15 23:04:04.652Repositorio Institucional Universidad Nacional de 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