Mostrar el registro sencillo del ítem
Optimal Integration of Photovoltaic Systems in Distribution Networks from a Technical, Financial, and Environmental Perspective
dc.contributor.author | Henao, Jhony Guzman | |
dc.contributor.author | Grisales-Noreña, Luis Fernando | |
dc.contributor.author | Restrepo-Cuestas, Bonie Johana | |
dc.contributor.author | Montoya, Oscar Danilo | |
dc.date.accessioned | 2023-05-25T20:12:41Z | |
dc.date.available | 2023-05-25T20:12:41Z | |
dc.date.issued | 2023-01-03 | |
dc.date.submitted | 2023-05-25 | |
dc.identifier.citation | Guzman-Henao, J.; Grisales-Noreña, L.F.; Restrepo-Cuestas, B.J.; Montoya, O.D. Optimal Integration of Photovoltaic Systems in Distribution Networks from a Technical, Financial, and Environmental Perspective. Energies 2023, 16, 562. https://doi.org/10.3390/en16010562 | spa |
dc.identifier.uri | https://hdl.handle.net/20.500.12585/11861 | |
dc.description.abstract | Due to the increasing demand for electricity around the world, different technologies have been developed to ensure the sustainability of each and every process involved in its production, transmission, and consumption. In addition to ensuring energy sustainability, these technologies seek to improve some of the characteristics of power systems and, in doing so, make them efficient from a financial, technical, and environmental perspective. In particular, solar photovoltaic (PV) technology is one of the power generation technologies that has had the most influence and development in recent years due to its easy implementation and low maintenance costs. Additionally, since PV systems can be located close to the load, power losses during distribution and transmission can be significantly reduced. However, in order to maximize the financial, technical, and environmental variables involved in the operation of an electrical system, a PV power generation project must guarantee the proper location and sizing of the generation sources. In the specialized literature, different studies have employed mathematical methods to determine the optimal location and size of generation sources. These methods model the operation of electrical systems and provide potential analysis scenarios following the deployment of solar PV units. The majority of such studies, however, do not assess the quality and repeatability of the solutions in short processing times. In light of this, the purpose of this study is to review the literature and contributions made in the field. | spa |
dc.format.extent | 19 páginas | |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Energies Vol. 16 No. 1 (2023) | spa |
dc.title | Optimal Integration of Photovoltaic Systems in Distribution Networks from a Technical, Financial, and Environmental Perspective | spa |
dcterms.bibliographicCitation | Rahman, A.; Farrok, O.; Haque, M.M. Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renew. Sustain. Energy Rev. 2022, 161, 112279. | spa |
dcterms.bibliographicCitation | Gutiérrez, A.S.; Morejón, M.B.; Eras, J.J.C.; Ulloa, M.C.; Martínez, F.J.R.; Rueda-Bayona, J.G. Data supporting the forecast of electricity generation capacity from non-conventional renewable energy sources in Colombia. Data Brief 2020, 28, 104949. | spa |
dcterms.bibliographicCitation | Schaube, P.; Ise, A.; Clementi, L. Distributed photovoltaic generation in Argentina: An analysis based on the technical innovation system framework. Technol. Soc. 2022, 68, 101839. | spa |
dcterms.bibliographicCitation | Kang, S.H.; Islam, F.; Tiwari, A.K. The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model. Struct. Chang. Econ. Dyn. 2019, 50, 90–101. | spa |
dcterms.bibliographicCitation | Londoño Posso, J.M.; Hincapié Isaza, R.A.; Gallego Rendón, R.A. Planeamiento de redes de baja tensión, utilizando un modelo trifásico. Cienc. E Ing. Neogranadina 2011, 21, 41–53. | spa |
dcterms.bibliographicCitation | Yoshizawa, S.; Yamamoto, Y.; Yoshinaga, J.; Hayashi, Y.; Sasaki, S.; Shigetou, T.; Nomura, H. Novel voltage control of multiple step voltage regulators in a distribution system. In Proceedings of the 2014 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2014, Istanbul, Turkey, 12–15 October 2014. | spa |
dcterms.bibliographicCitation | Ackermann, T.; Andersson, G.; Söder, L. Distributed generation: A definition. Electr. Power Syst. Res. 2001, 57, 195–204 | spa |
dcterms.bibliographicCitation | Das, U.K.; Tey, K.S.; Seyedmahmoudian, M.; Mekhilef, S.; Idris, M.Y.I.; Deventer, W.V.; Horan, B.; Stojcevski, A. Forecasting of photovoltaic power generation and model optimization: A review. Renew. Sustain. Energy Rev. 2018, 81, 912–928 | spa |
dcterms.bibliographicCitation | Balamurugan, K.; Srinivasan, D.; Reindl, T. Impact of distributed generation on power distribution systems. Energy Procedia 2012, 25, 93–100. | spa |
dcterms.bibliographicCitation | Bayer, Christophe Pierre, Fionna Klasen, and Hubertus Adam. 2007. “Association of Trauma and PTSD Symptoms with Openness to Reconciliation and Feelings of Revenge Among Former Ugandan and Congolese Child Soldiers.” Journal of the American Medical Association 298 (5): 555-559. https://doi.org/10.1001/jama.298.5.555 8. | spa |
dcterms.bibliographicCitation | Hassan, A.S.; Othman, E.S.A.; Bendary, F.M.; Ebrahim, M.A. Optimal integration of distributed generation resources in active distribution networks for techno-economic benefits. Energy Rep. 2020, 6, 3462–3471. | spa |
dcterms.bibliographicCitation | Ackermann, T.; Andersson, G.; Söder, L. Distributed generation: A definition. Electr. Power Syst. Res. 2001, 57, 195–204. | spa |
dcterms.bibliographicCitation | Antonio, M.; Camargo, C.; Javier, W.; Ramirez, H. Atlas Potencial Hidroenergético de Colombia. UPME. 2015; pp. 1–24. ISBN 9789587168471. Available online: http://bdigital.upme.gov.co/handle/001/1336 (accessed on 8 October 2022). | spa |
dcterms.bibliographicCitation | Fang, J.; Li, G.; Liang, X.; Zhou, M. An optimal control strategy for reactive power in wind farms consisting of VSCF DFIG wind turbine generator systems. In Proceedings of the DRPT 2011—2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, Weihai, China, 6–9 July 2011; pp. 1709–1715. | spa |
dcterms.bibliographicCitation | Clementi, L.V.; Jacinto, G.P. Energía distribuida: Oportunidades y desafíos en Argentina. Let. Verdes Rev. Latinoam. Estud. Socioambientales 2021, 29, 48–64. | spa |
dcterms.bibliographicCitation | UPME. Resolución 703, 2018. Bogotá, Colombia. Dirección de la Unidad de Planeación Minero-Energética. Available online: https://gestornormativo.creg.gov.co/gestor/entorno/docs/resolucion_upme_0703_2018.htm (accessed on 15 August 2022). | spa |
dcterms.bibliographicCitation | Rondina, J.M.; Martins, N.L.; Alves, M.B. Technology Alternative for Enabling Distributed Generation. IEEE Lat. Am. Trans. 2016, 14, 4089–4096. | spa |
dcterms.bibliographicCitation | Akinyele, D.O.; Rayudu, R.K.; Nair, N.K. Global progress in photovoltaic technologies and the scenario of development of solar panel plant and module performance estimation—Application in Nigeria. Renew. Sustain. Energy Rev. 2015, 48, 112–139. | spa |
dcterms.bibliographicCitation | Ahmed, M.T.; Gonçalves, T.; Tlemcani, M. Single diode model parameters analysis of photovoltaic cell. In Proceedings of the 2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA), Birmingham, UK, 20–23 November 2016; Volume 5, pp. 396–40 | spa |
dcterms.bibliographicCitation | Saeednia, M.M.; Ezoji, H. Reviewing the Effect of Distributed Generation Interconnections on Distribution Systems. 23rd International Power System Conference (PSC 2007). pp. 1–10. Available online: https://civilica.com/doc/130952/ (accessed on 7 July 2022). | spa |
dcterms.bibliographicCitation | Jannat, M.B.; Savi´c, A.S. Optimal capacitor placement in distribution networks regarding uncertainty in active power load and distributed generation units production. IET Gener. Transm. Distrib. 2016, 10, 3060–3067. | spa |
dcterms.bibliographicCitation | Bianco, V.; Manca, O.; Nardini, S. Electricity consumption forecasting in Italy using linear regression models. Energy 2009, 34, 1413–1421 | spa |
dcterms.bibliographicCitation | Zhu, Y.; Hjalmarsson, H. The Box-Jenkins Steiglitz-McBride algorithm. Automatica 2016, 65, 170–182 | spa |
dcterms.bibliographicCitation | Sun, H.; Qiu, Y.; Li, J. A novel artificial neural network model for wide-band random fatigue life prediction. Int. J. Fatigue 2022, 157, 106701 | spa |
dcterms.bibliographicCitation | Yumurtaci, Z.; Asmaz, E. Electric energy demand of Turkey for the year 2050. Energy Sources 2004, 26, 1157–1164. | spa |
dcterms.bibliographicCitation | kaytez, F.; Taplamacioglu, M.C.; Cam, E.; Hardalac, F. Forecasting electricity consumption: A comparison of regression analysis, neural networks and least squares support vector machines. Int. J. Electr. Power Energy Syst. 2015, 67, 431–438. | spa |
dcterms.bibliographicCitation | Diaz-Acevedo, J.A.; Grisales-Noreña, L.F.; Escobar, A. A method for estimating electricity consumption patterns of buildings to implement Energy Management Systems. J. Build. Eng. 2019, 25, 100774 | spa |
dcterms.bibliographicCitation | Velez Marin, V.M. Planeamiento de Sistemas Secundarios de Distribución Considerando el Concepto de Demanda Diversificada; Universidad Tecnológica de Pereira: Pereira, Colombia, 2013. | spa |
dcterms.bibliographicCitation | Inman, R.H.; Pedro, H.T.; Coimbra, C.F. Solar forecasting methods for renewable energy integration. Prog. Energy Combust. Sci. 2013, 39, 535–576 | spa |
dcterms.bibliographicCitation | Beltrán, J.C.; Aristizábal, A.J.; López, A.; Castaneda, M.; Zapata, S.; Ivanova, Y. Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems. Energy Rep. 2020, 6, 88–10 | spa |
dcterms.bibliographicCitation | Rahmani-Andebili, M. Stochastic, adaptive, and dynamic control of energy storage systems integrated with renewable energy sources for power loss minimization. Renew. Energy 2017, 113, 1462–1471 | spa |
dcterms.bibliographicCitation | Alencar, D.B.D.; Affonso, C.D.M.; Oliveira, R.C.L.D.; Rodríguez, J.L.M.; Leite, J.C.; Filho, J.C.R. Different Models for Forecasting Wind Power Generation: Case Study. Energies 2017, 10, 1976. | spa |
dcterms.bibliographicCitation | Zhou, K.; Fu, C.; Yang, S. Big data driven smart energy management: From big data to big insights. Renew. Sustain. Energy Rev. 2016, 56, 215–225. | spa |
dcterms.bibliographicCitation | Hernandez, J.A.; Velasco, D.; Trujillo, C.L. Analysis of the effect of the implementation of photovoltaic systems like option of distributed generation in Colombia. Renew. Sustain. Energy Rev. 2011, 15, 2290–2298. | spa |
dcterms.bibliographicCitation | Montoya, O.D.; Gil-González, W. On the numerical analysis based on successive approximations for power flow problems in AC distribution systems. Electr. Power Syst. Res. 2020, 187, 106454. | spa |
dcterms.bibliographicCitation | Barrero Gonzalez, F. Sistemas de Energia Electrica; Editorial Paraninfo S.A.: Madrid, Spain, 2004 | spa |
dcterms.bibliographicCitation | Grainger, J.J.; Stevenson, W.D. Analisis de Sistemas de Potencia; McGraw-Hill Mexico: Mexico City, Mexico, 1996. | spa |
dcterms.bibliographicCitation | Mercado, D. Análisis de Sensibilidad del Resultado del Flujo de Carga en Sistemas de Distribucion ante Incertidumbre en el Modelo Eléctrico; Facultad de Ingenierias, Universidad Nacional de Colombia: Bogota, Colombia, 2011; p. 135 | spa |
dcterms.bibliographicCitation | Universidad Nacional Autónoma de México (UNAM); González, P.; Cárdenas, M.; Pinilla, V.; Salazar, A.; Tovar, V. Métodos iterativos de Jacobi y Gauss–Seidel. Ingenieria. Unam 2019, 1–9. Available online: https://www.ingenieria.unam.mx/pinilla/PE1 05117/pdfs/tema3/3-3_metodos_jacobi_gauss-seidel.pdf (accessed on 10 October 2022). | spa |
dcterms.bibliographicCitation | Tapasco Suarez, K.P. Aproximaciones al Flujo de Carga en Sistemas de Distribución; Universidad Tecnologica de Pereira: Pereira, Colombia, 2017. | spa |
dcterms.bibliographicCitation | Vigil, J.C. Application of Numerical Methods To Solve Nonlinear Equations for Sea Wave Modeling. Curso CE0607 Análisis Numérico. 2011. Available online: https://docplayer.es/48346600-Application-of-numerical-methods-to-solve-nonlinear equations-for-sea-wave-modeling.html (accessed on 5 May 2022). | spa |
dcterms.bibliographicCitation | Grainger, J.J. Power System Analysis; McGraw-Hill: New York, NY, USA, 1999. | spa |
dcterms.bibliographicCitation | Dinh, H.N.; Yoon, Y.T. A novel method for solving the divergence of power flow and controlling voltage in integrated distributed generators network. IEEE Power Energy Soc. Gen. Meet. 2012, 1–5. | spa |
dcterms.bibliographicCitation | Sharma, D.; Singh, P. Optimal Planning of Distribute Energy Resources Sizing and Location Problem—A Review. In Proceedings of the 2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020, Coimbatore, India, 15–17 July 2020; pp. 500–504 | spa |
dcterms.bibliographicCitation | Kansal, S.; Kumar, V.; Tyagi, B. Optimal placement of different type of DG sources in distribution networks. Int. J. Electr. Power Energy Syst. 2013, 53, 752–760 | spa |
dcterms.bibliographicCitation | Ghosh, S.; Ghoshal, S.P.; Ghosh, S. Optimal sizing and placement of distributed generation in a network system. Int. J. Electr. Power Energy Syst. 2010, 32, 849–856. | spa |
dcterms.bibliographicCitation | Rendon, R.A.G.; Zuluaga, A.H.E.; Ocampo, E.M.T. Tecnicas Metaheuristicas de Optimizacion; Universidad Tecnologica de Pereira: Pereira, Colombia, 2008. | spa |
dcterms.bibliographicCitation | Georgilakis, P.S.; Hatziargyriou, N.D. Optimal distributed generation placement in power distribution networks: Models, methods, and future research. IEEE Trans. Power Syst. 2013, 28, 3420–3428. | spa |
dcterms.bibliographicCitation | Noreña, L.F.G.; Cuestas, B.J.R.; Ramirez, F.E.J. Ubicación y dimensionamiento de generación distribuida: Una revisión. Cienc. E Ing. Neogranadina 2017, 27, 157–176. | spa |
dcterms.bibliographicCitation | Wang, C.; Nehrir, M.H. Analytical approaches for optimal placement of distributed generation sources in power systems. IEEE Trans. Power Syst. 2004, 19, 2068–2076. | spa |
dcterms.bibliographicCitation | Khalesi, N.; Rezaei, N.; Haghifam, M.R. DG allocation with application of dynamic programming for loss reduction and reliability improvement. Int. J. Electr. Power Energy Syst. 2011, 33, 288–295. | spa |
dcterms.bibliographicCitation | Singh, B.; Mukherjee, V.; Tiwari, P. A survey on impact assessment of DG and FACTS controllers in power systems. Renew. Sustain. Energy Rev. 2015, 42, 846–882 | spa |
dcterms.bibliographicCitation | Porkar, S.; Poure, P.; Abbaspour-Tehrani-fard, A.; Saadate, S. Optimal allocation of distributed generation using a two-stage multi-objective mixed-integer-nonlinear programming. Eur. Trans. Electr. Power 2011, 21, 1072–1087 | spa |
dcterms.bibliographicCitation | Zhou, Z.; Zhang, J.; Liu, P.; Li, Z.; Georgiadis, M.C.; Pistikopoulos, E.N. A two-stage stochastic programming model for the optimal design of distributed energy systems. Appl. Energy 2013, 103, 135–144. | spa |
dcterms.bibliographicCitation | Foster, J.D.; Berry, A.M.; Boland, N.; Waterer, H. Comparison of mixed-integer programming and genetic algorithm methods for distributed generation planning. IEEE Trans. Power Syst. 2014, 29, 833–843. | spa |
dcterms.bibliographicCitation | Liu, L.; Mu, H.; Song, Y.; Luo, H.; Li, X.; Wu, F. The equilibrium generalized assignment problem and genetic algorithm. Appl. Math. Comput. 2012, 218, 6526–6535. | spa |
dcterms.bibliographicCitation | Mohammadi, M.A.Y.; Faramarzi, M. PSO algorithm for sitting and sizing of distributed generation to improve voltage profile and decreasing power losses. In Proceedings of the 17th Conference on Electrical Power Distribution, Tehran, Iran, 2–3 May 2012; pp. 1–5. | spa |
dcterms.bibliographicCitation | Amritha, K.; Rajagopal, V.; Raju, K.N.; Arya, S.R. Ant lion algorithm for optimized controller gains for power quality enrichment of off-grid wind power harnessing units. Chin. J. Electr. Eng. 2020, 6, 85–97. [CrossRef] | spa |
dcterms.bibliographicCitation | Wang, L.; Shi, Z.; Wang, Z. Reactive Power Optimization for Power System with Distributed Generations Using PSO Hybrid SCA Algorithm. In Proceedings of the IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS), Suzhou, China, 14–16 May 2021; pp. 248–253. | spa |
dcterms.bibliographicCitation | Gözel, T.; Hocaoglu, M.H. An analytical method for the sizing and siting of distributed generators in radial systems. Electr. Power Syst. Res. 2009, 79, 912–918. | spa |
dcterms.bibliographicCitation | Acharya, N.; Mahat, P.; Mithulananthan, N. An analytical approach for DG allocation in primary distribution network. Int. J. Electr. Power Energy Syst. 2006, 28, 669–678 | spa |
dcterms.bibliographicCitation | Gil-González, W.; Garces, A.; Montoya, O.D.; Hernández, J.C. A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks. Appl. Sci. 2021, 11, 627 | spa |
dcterms.bibliographicCitation | Naik, S.N.G.; Khatod, D.K.; Sharma, M.P. Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks. IET Gener. Transm. Distrib. 2015, 9, 209–220. | spa |
dcterms.bibliographicCitation | Mahmoud, K.; Yorino, N.; Ahmed, A. Optimal Distributed Generation Allocation in Distribution Systems for Loss Minimization. IEEE Trans. Power Syst. 2016, 31, 960–969 | spa |
dcterms.bibliographicCitation | Koutsoukis, N.C.; Siagkas, D.O.; Georgilakis, P.S.; Hatziargyriou, N.D. Online Reconfiguration of Active Distribution Networks for Maximum Integration of Distributed Generation. IEEE Trans. Autom. Sci. Eng. 2017, 14, 437–448. | spa |
dcterms.bibliographicCitation | Khoa, T.Q.D.; Binh, P.; Tran, H. Optimizing location and sizing of distributed generation in distribution systems. In Proceedings of the 2006 IEEE PES Power Systems Conference and Exposition, Atlanta, GA, USA, 29 October–1 November 2006; pp. 725–732. | spa |
dcterms.bibliographicCitation | Abdel-Akher, M.; Ali, A.; Eid, A.; El-Kishky, H. Optimal size and location of distributed generation unit for voltage stability enhancement. In Proceedings of the 2011 IEEE Energy Conversion Congress and Exposition, Detroit, MI, USA, 9–13 October 2011; pp. 104–108. | spa |
dcterms.bibliographicCitation | Kaur, S.; Kumbhar, G.; Sharma, J. A MINLP technique for optimal placement of multiple DG units in distribution systems. Int. J. Electr. Power Energy Syst. 2014, 63, 609–617. | spa |
dcterms.bibliographicCitation | Ouyang, W.; Cheng, H.; Zhang, X.; Yao, L. Distribution network planning method considering distributed generation for peak cutting. Energy Convers. Manag. 2010, 51, 2394–2401. | spa |
dcterms.bibliographicCitation | Mohamed, I.A.; Kowsalya, M. Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization. Swarm Evol. Comput. 2014, 15, 58–65. | spa |
dcterms.bibliographicCitation | García-Muñoz, F.; Díaz-González, F.; Corchero, C. A two-stage stochastic programming model for the sizing and location of DERs considering electric vehicles and demand response. Sustain. Energy Grids Networks 2022, 30, 100624. | spa |
dcterms.bibliographicCitation | Wu, D.; Ma, X.; Huang, S.; Fu, T.; Balducci, P. Stochastic optimal sizing of distributed energy resources for a cost-effective and resilient Microgrid. Energy 2020, 198, 117284. | spa |
dcterms.bibliographicCitation | Bacca, E.J.M.; Knight, A.; Trifkovic, M. Optimal land use and distributed generation technology selection via geographic-based multicriteria decision analysis and mixed-integer programming. Sustain. Cities Soc. 2020, 55, 102055. | spa |
dcterms.bibliographicCitation | García-Muñoz, F.; Díaz-González, F.; Corchero, C. A novel algorithm based on the combination of AC-OPF and GA for the optimal sizing and location of DERs into distribution networks. Sustain. Energy Grids Networks 2021, 27, 100497. | spa |
dcterms.bibliographicCitation | Gautam, M.; Bhusal, N.; Benidris, M. A Cooperative Game Theory-based Approach to Sizing and Siting of Distributed Energy Resources. In Proceedings of the 2021 North American Power Symposium (NAPS), College Station, TX, USA, 14–16 November 2021; pp. 1–6. | spa |
dcterms.bibliographicCitation | Montoya, O.D.; Grisales-Noreña, L.F.; Gil-González, W.; Alcalá, G.; Hernandez-Escobedo, Q. Optimal location and sizing of PV sources in DC networks for minimizing greenhouse emissions in diesel generators. Symmetry 2020, 12, 322 | spa |
dcterms.bibliographicCitation | Molina-Martin, F.; Montoya, O.D.; Grisales-Noreña, L.F.; Hernández, J.C.; Ramírez-Vanegas, C.A. Simultaneous minimization of energy losses and greenhouse gas emissions in ac distribution networks using bess. Electronics 2021, 10, 1002. | spa |
dcterms.bibliographicCitation | Qian, K.; Zhou, C.; Yuan, Y.; Shi, X.; Allan, M. Analysis of the environmental benefits of distributed generation. In Proceedings of the 2008 IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, IEEE, Pittsburgh, PA, USA, 20–24 July 2008; pp. 1–5 | spa |
datacite.rights | http://purl.org/coar/access_right/c_abf2 | spa |
oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.hasversion | info:eu-repo/semantics/draft | spa |
dc.identifier.doi | https://doi.org/10.3390/en16010562 | |
dc.subject.keywords | Sustainability | spa |
dc.subject.keywords | Generation | spa |
dc.subject.keywords | Photovoltaic solar energy | spa |
dc.subject.keywords | Power losses | spa |
dc.subject.keywords | Location | spa |
dc.subject.keywords | Sizing | spa |
dc.subject.keywords | Mathematical methods | spa |
dc.subject.keywords | Repeatability | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.cc | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.identifier.instname | Universidad Tecnológica de Bolívar | spa |
dc.identifier.reponame | Repositorio Universidad Tecnológica de Bolívar | spa |
dc.publisher.place | Cartagena de Indias | spa |
dc.subject.armarc | LEMB | |
dc.type.spa | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
dc.audience | Público general | spa |
dc.publisher.sede | Campus Tecnológico | spa |
oaire.resourcetype | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
Productos de investigación [1453]
Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.