An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia

Solar and wind energy systems, without storage, cannot satisfy variable load demands, but their combined use can help to solve the problem of the balance between generation and consumption. Energetic complementarity studies are useful to evaluate the viability of the use of two or more renewable ene...

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Autores:
Peña Gallardo, Rafael
Ospino C., Adalberto
Medina Ríos, Aurelio
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/6898
Acceso en línea:
https://hdl.handle.net/11323/6898
https://doi.org/10.3390/en13051033
https://repositorio.cuc.edu.co/
Palabra clave:
Energetic complementarity
Image processing algorithms
Resource maps
Solar energy
Wind energy
Complementariedad energética
Algoritmos de procesamiento de imágenes
Mapas de recursos
Energía solar
Energía eólica
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_2b426c59465586e71250d7d3b43336ed
oai_identifier_str oai:repositorio.cuc.edu.co:11323/6898
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
dc.title.translated.spa.fl_str_mv Un método basado en el procesamiento de imágenes para evaluar la complementariedad energética mensual de la energía solar y eólica en Colombia
title An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
spellingShingle An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
Energetic complementarity
Image processing algorithms
Resource maps
Solar energy
Wind energy
Complementariedad energética
Algoritmos de procesamiento de imágenes
Mapas de recursos
Energía solar
Energía eólica
title_short An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
title_full An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
title_fullStr An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
title_full_unstemmed An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
title_sort An image processing-based method to assess the monthly energetic complementarity of solar and wind energy in Colombia
dc.creator.fl_str_mv Peña Gallardo, Rafael
Ospino C., Adalberto
Medina Ríos, Aurelio
dc.contributor.author.spa.fl_str_mv Peña Gallardo, Rafael
Ospino C., Adalberto
Medina Ríos, Aurelio
dc.subject.spa.fl_str_mv Energetic complementarity
Image processing algorithms
Resource maps
Solar energy
Wind energy
Complementariedad energética
Algoritmos de procesamiento de imágenes
Mapas de recursos
Energía solar
Energía eólica
topic Energetic complementarity
Image processing algorithms
Resource maps
Solar energy
Wind energy
Complementariedad energética
Algoritmos de procesamiento de imágenes
Mapas de recursos
Energía solar
Energía eólica
description Solar and wind energy systems, without storage, cannot satisfy variable load demands, but their combined use can help to solve the problem of the balance between generation and consumption. Energetic complementarity studies are useful to evaluate the viability of the use of two or more renewable energy sources with high variability in a specific interval of time in a determined region. In this paper, the monthly energetic complementarity study of solar and wind resources of Colombia is carried out. A novel approach to conduct the study is proposed. A dataset with the average monthly solar radiation and wind speed values is obtained from high-resolution images of renewable resources maps, using image processing algorithms. Then, the dataset is used to calculate the energetic complementarity of the sources employing the negative of the Pearson correlation coefficient. The obtained values are transformed to energetic complementarity maps, previously eliminating the protected areas. The obtained results show that there is a good energetic complementarity in the north and northeastern regions of the country throughout the year. The results indicate that projects related to the joint use of solar and wind generation systems could be developed in these regions.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-08-10T19:19:36Z
dc.date.available.none.fl_str_mv 2020-08-10T19:19:36Z
dc.date.issued.none.fl_str_mv 2020-02-21
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
format http://purl.org/coar/resource_type/c_6501
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 1996-1073
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/6898
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.3390/en13051033
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 1996-1073
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/6898
https://doi.org/10.3390/en13051033
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
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8, 729. [CrossRef]
7. Peña Gallardo, R.; Ospino Castro, A.; Segundo Ramirez, J.; Rodriguez Hernández, A.; Noriega Angarita, E.; Munoz Maldonado, Y.A. Economic and energy analysis of small capacity grid-connected hybrid photovoltaic-wind systems in Mexico. Int. J. Energy Econ. Policy 2020, 10, 7–17. [CrossRef]
8. Pagola, V.; Peña, R.; Segundo, J.; Ospino, A. Rapid Prototyping of a Hybrid PV–Wind Generation System Implemented in a Real-Time Digital Simulation Platform and Arduino. Electronics 2019, 8, 102. [CrossRef]
9. Jurasz, J.; Canales, F.A.; Kies, A.; Guezgouz, M.; Beluco, A. A Review on the Complementarity of Renewable Energy Sources: Concept, Metrics, Application and Future Research Directions. Sol. Energy 2020, 195, 703–724. [CrossRef]
10. Bagatini, M.; Benevit, M.G.; Beluco, A.; Risso, A. Complementarity in Time between Hydro, Wind and Solar Energy Resources in the State of Rio Grande Do Sul, in Southern Brazil. Energy Power Eng. 2017, 9, 515–526. [CrossRef]
11. Beluco, A.; de Souza, P.K.; Krenzinger, A. A Dimensionless Index Evaluating the Time Complementarity between Solar and Hydraulic Energies. Renew. Energy 2008, 33, 2157–2165. [CrossRef]
12. François, B.; Borga, M.; Creutin, J.D.; Hingray, B.; Raynaud, D.; Sauterleute, J.F. Complementarity between Solar and Hydro Power: Sensitivity Study to Climate Characteristics in Northern-Italy. Renew. Energy 2016, 86, 543–553. [CrossRef]
13. Monforti, F.; Huld, T.; Bódis, K.; Vitali, L.; D’Isidoro, M.; Lacal-Arántegui, R. Assessing Complementarity of Wind and Solar Resources for Energy Production in Italy. A Monte Carlo Approach. Renew. Energy 2014, 63, 576–586. [CrossRef]
14. Miglietta, M.M.; Huld, T.; Monforti-Ferrario, F. Local Complementarity of Wind and Solar Energy Resources over Europe: An Assessment Study from a Meteorological Perspective. J. Appl. Meteorol. Climatol. 2017, 56, 217–234. [CrossRef]
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20. Xu, L.; Wang, Z.; Liu, Y. The Spatial and Temporal Variation Features of Wind-Sun Complementarity in China. Energy Convers. Manag. 2017, 154, 138–148. [CrossRef]
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23. Shaner, M.R.; Davis, S.J.; Lewis, N.S.; Caldeira, K. Geophysical Constraints on the Reliability of Solar and Wind Power in the United States. Energy Environ. Sci. 2018, 11, 914–925. [CrossRef]
24. Jurasz, J.; D ˛abek, P.B.; Ka ´zmierczak, B.; Kies, A.; Wdowikowski, M. Large Scale Complementary Solar and Wind Energy Sources Coupled with Pumped-Storage Hydroelectricity for Lower Silesia (Poland). Energy 2018, 161, 183–192. [CrossRef]
25. Bett, P.E.; Thornton, H.E. The Climatological Relationships between Wind and Solar Energy Supply in Britain. Renew. Energy 2016, 87, 96–110. [CrossRef]
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27. Dos Anjos, P.S.; Alves Da Silva, A.S.; Stoši´c, B.; Stoši´c, T. Long-Term Correlations and Cross-Correlations in Wind Speed and Solar Radiation Temporal Series from Fernando de Noronha Island, Brazil. Phys. A Stat. Mech. Appl. 2015, 424, 90–96. [CrossRef]
28. Li, W.; Stadler, S.; Ramakumar, R. Modeling and Assessment of Wind and Insolation Resources with a Focus on Their Complementary Nature: A Case Study of Oklahoma. Ann. Assoc. Am. Geogr. 2011, 101, 717–729. [CrossRef]
29. Vergara, W.; Deeb, A.; Toba, N.; Cramton, P.; Leino, I.; Benoit, P. Wind Energy in Colombia: A Framework for Market Entry; World Bank: Washington, DC, USA, 2010. [CrossRef]
30. Rodríguez-Urrego, D.; Rodríguez-Urrego, L. Photovoltaic Energy in Colombia: Current Status, Inventory, Policies and Future Prospects. Renew. Sustain. Energy Rev. 2018, 92, 160–170. [CrossRef]
31. SIEL. Informe Mensual de Variables de Generación y del Mercado Electrico Colombiano-Marzo de 2018; Ministry Minas y Energía: Bogota, Colombia, 2018.
32. Olaya, Y.; Arango-Aramburo, S.; Larsen, E.R. How Capacity Mechanisms Drive Technology Choice in Power Generation: The Case of Colombia. Renew. Sustain. Energy Rev. 2016, 56, 563–571. [CrossRef]
33. Paez, A.F.; Maldonado, Y.M.; Castro, A.O.; Hernandez, N.; Conde, E.; Pacheco, L.; Gonzalez, W.; Sotelo, O. Future Scenarios and Trends of Energy Demand in Colombia Using Long-Range Energy Alternative Planning. Int. J. Energy Econ. Policy 2017, 7, 178–190.
34. Han, S.; Zhang, L.N.; Liu, Y.Q.; Zhang, H.; Yan, J.; Li, L.; Lei, X.H.; Wang, X. Quantitative Evaluation Method for the Complementarity of Wind–Solar–Hydro Power and Optimization of Wind–Solar Ratio. Appl. Energy 2019, 236, 973–984. [CrossRef]
35. Gómez-Navarro, T.; Ribó-Pérez, D. Assessing the Obstacles to the Participation of Renewable Energy Sources in the Electricity Market of Colombia. Renew. Sustain. Energy Rev. 2018, 90, 131–141. [CrossRef]
36. IDEAM. Atlas Interactivo de Recursos Naturales de Colombia; Instituto de Hidrología, Meteorología y Estudios Ambientales: Bogota, Colombia, 2019.
37. Ordóñez, G.; Osma, G.; Vergara, P.; Rey, J. Wind and Solar Energy Potential Assessment for Development of Renewables Energies Applications in Bucaramanga, Colombia. IOP Conf. Ser. Mater. Sci. Eng. 2014, 59. [CrossRef]
38. Castillo, Y.; Gutiérrez, M.C.; Vanegas-Chamorro, M.; Valencia, G.; Villicaña, E. Rol de Las Fuentes No Convencionales de Energía En El Sector Eléctrico Colombiano. Prospectiva 2015, 13, 39–51. [CrossRef]
39. Instituto de Hidrología Meteorología y Estudios Ambientales. Atlas de Radiación Solar, Ultravioleta y Ozono de Colombia; Instituto de Hidrología Meteorología y Estudios Ambientales: Bogota, Colombia, 2015. [CrossRef]
40. Banda, D.; Pena, R.; Gutierrez, G.; Juarez, E.; Visairo, N.; Nunez, C. Feasibility Assessment of the Installation of a Photovoltaic System as a Battery Charging Center in a Mexican Mining Company. In Proceedings of the 2014 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC 2014), Ixtapa, Mexico, 5–7 November 2014. [CrossRef]
41. De la Cruz Buelvas, J.; Valencia Ochoa, G.; Vanegas Chamorro, M. Statistical Study of Wind Speed and Direction in the Departments of Atlántico and Bolivar in Colombia. Ingeniare 2018, 26, 319–328. [CrossRef]
42. Congreso de Colombia. Ley 1715 de 2014—Por Medio de la Cual se Regula la Integración de las Energías Renovables no Convencionales al Sistema Energético Nacional; Congreso de Colombia: Bogota, Colombia, 2014.
43. UPME. Informe de gestión 2018, Ministerio de Minas y Energía, República de Colombia; Ministry Minas y Energía: Bogota, Colombia, 2018.
44. UPME, IDEAM. Atlas de Viento y Enegía Eólica de Colombia; UPME-IDEAM: Bogota, Colombia, 2010.
45. Hernandez, A.; Pena, R.; Mendez, W.; Visairo, N.; Nunez, C. Wind Resource Assessment in the Surroundings of San Luis Potosi, Mexico. In Proceedings of the 2013 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC 2013), Mexico City, Mexico, 13–15 November 2013. [CrossRef]
46. Canavire-Bacarreza, G.; Diaz-Gutierrez, J.E.; Hanauer, M.M. Unintended Consequences of Conservation: Estimating the Impact of Protected Areas on Violence in Colombia. J. Environ. Econ. Manag. 2018, 89, 46–70. [CrossRef]
47. Congreso de Colombia. Ley 165 de 1994—Por Medio de la Cual se Aprueba el “Convenio Sobre la Diversidad Biológica; Congreso de Colombia: Bogota, Colombia, 1994.
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49. SINAP. Mapa SINAP—Sistema Nacional de Áreas Protegidas de Colombia; Sistema Nacional de Áreas Protegidas: Bogota, Colombia, 2018.
50. Peña Gallardo, R.; Ospino Castro, A. An Assessment Study of the Monthly Complementarity of Renewable Energy Resources in Colombia. In Proceedings of the 7th International Workshop Advances in Cleaner Production, Barranquilla, Colombia, 21–22 June 2018; pp. 1–11.
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spelling Peña Gallardo, Rafael28f1b9addfd74d20355f9353d97b4bb1Ospino C., Adalbertodc979344fb023fb42436d7b9e8e53d19Medina Ríos, Aurelio11c0d6ee1e6e0e92324b246d71f05fe72020-08-10T19:19:36Z2020-08-10T19:19:36Z2020-02-211996-1073https://hdl.handle.net/11323/6898https://doi.org/10.3390/en13051033Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Solar and wind energy systems, without storage, cannot satisfy variable load demands, but their combined use can help to solve the problem of the balance between generation and consumption. Energetic complementarity studies are useful to evaluate the viability of the use of two or more renewable energy sources with high variability in a specific interval of time in a determined region. In this paper, the monthly energetic complementarity study of solar and wind resources of Colombia is carried out. A novel approach to conduct the study is proposed. A dataset with the average monthly solar radiation and wind speed values is obtained from high-resolution images of renewable resources maps, using image processing algorithms. Then, the dataset is used to calculate the energetic complementarity of the sources employing the negative of the Pearson correlation coefficient. The obtained values are transformed to energetic complementarity maps, previously eliminating the protected areas. The obtained results show that there is a good energetic complementarity in the north and northeastern regions of the country throughout the year. The results indicate that projects related to the joint use of solar and wind generation systems could be developed in these regions.Los sistemas de energía solar y eólica, sin almacenamiento, no pueden satisfacer las demandas de carga variable, pero su uso combinado puede ayudar a resolver el problema del equilibrio entre generación y consumo. Los estudios de complementariedad energética son útiles para evaluar la viabilidad del uso de dos o más fuentes de energía renovable con alta variabilidad en un intervalo de tiempo específico en una región determinada. En este artículo, el estudio mensual de complementariedad energética de los recursos solar y eólico de Colombia se lleva a cabo. Se propone un enfoque novedoso para realizar el estudio. Un conjunto de datos con el promedio Los valores mensuales de radiación solar y velocidad del viento se obtienen a partir de imágenes de alta resolución de renovables. mapas de recursos, utilizando algoritmos de procesamiento de imágenes. Luego, el conjunto de datos se utiliza para calcular el complementariedad energética de las fuentes empleando el negativo del coeficiente de correlación de Pearson. Los valores obtenidos se transforman en mapas de complementariedad energética, eliminando previamente la áreas protegidas. Los resultados obtenidos muestran que existe una buena complementariedad energética en el regiones del norte y noreste del país durante todo el año. Los resultados indican que los proyectos relacionados con el uso conjunto de sistemas de generación solar y eólica podrían desarrollarse en estas regiones.engCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Energieshttps://www.mdpi.com/1996-1073/13/5/1033/htmEnergetic complementarityImage processing algorithmsResource mapsSolar energyWind energyComplementariedad energéticaAlgoritmos de procesamiento de imágenesMapas de recursosEnergía solarEnergía eólicaAn image processing-based method to assess the monthly energetic complementarity of solar and wind energy in ColombiaUn método basado en el procesamiento de imágenes para evaluar la complementariedad energética mensual de la energía solar y eólica en ColombiaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1. Sorrell, S. Reducing Energy Demand: A Review of Issues, Challenges and Approaches. Renew. Sustain. Energy Rev. 2015, 47, 74–82. [CrossRef]2. Claudia Roldán, M.; Martínez, M.; Peña, R. Scenarios for a Hierarchical Assessment of the Global Sustainability of Electric Power Plants in México. Renew. Sustain. Energy Rev. 2014, 33, 154–160. [CrossRef]3. Wei, M.; Patadia, S.; Kammen, D.M. Putting Renewables and Energy Efficiency to Work: How Many Jobs Can the Clean Energy Industry Generate in the US? Energy Policy 2010, 38, 919–931. [CrossRef]4. Ellabban, O.; Abu-Rub, H.; Blaabjerg, F. Renewable Energy Resources: Current Status, Future Prospects and Their Enabling Technology. Renew. Sustain. Energy Rev. 2014, 39, 748–764. [CrossRef]5. Dincer, I. Renewable Energy and Sustainable Development: A Crucial Review. Renew. Sustain. Energy Rev. 2000, 4, 157–175. [CrossRef]6. Zsiborács, H.; Baranyai, N.H.; Vincze, A.; Zentkó, L.; Birkner, Z.; Máté, K.; Pintér, G. Intermittent Renewable Energy Sources: The Role of Energy Storage in the European Power System of 2040. Electronics 2019,8, 729. [CrossRef]7. Peña Gallardo, R.; Ospino Castro, A.; Segundo Ramirez, J.; Rodriguez Hernández, A.; Noriega Angarita, E.; Munoz Maldonado, Y.A. Economic and energy analysis of small capacity grid-connected hybrid photovoltaic-wind systems in Mexico. Int. J. Energy Econ. Policy 2020, 10, 7–17. [CrossRef]8. Pagola, V.; Peña, R.; Segundo, J.; Ospino, A. Rapid Prototyping of a Hybrid PV–Wind Generation System Implemented in a Real-Time Digital Simulation Platform and Arduino. Electronics 2019, 8, 102. [CrossRef]9. Jurasz, J.; Canales, F.A.; Kies, A.; Guezgouz, M.; Beluco, A. A Review on the Complementarity of Renewable Energy Sources: Concept, Metrics, Application and Future Research Directions. Sol. Energy 2020, 195, 703–724. [CrossRef]10. Bagatini, M.; Benevit, M.G.; Beluco, A.; Risso, A. Complementarity in Time between Hydro, Wind and Solar Energy Resources in the State of Rio Grande Do Sul, in Southern Brazil. Energy Power Eng. 2017, 9, 515–526. [CrossRef]11. Beluco, A.; de Souza, P.K.; Krenzinger, A. A Dimensionless Index Evaluating the Time Complementarity between Solar and Hydraulic Energies. Renew. Energy 2008, 33, 2157–2165. [CrossRef]12. François, B.; Borga, M.; Creutin, J.D.; Hingray, B.; Raynaud, D.; Sauterleute, J.F. Complementarity between Solar and Hydro Power: Sensitivity Study to Climate Characteristics in Northern-Italy. Renew. Energy 2016, 86, 543–553. [CrossRef]13. Monforti, F.; Huld, T.; Bódis, K.; Vitali, L.; D’Isidoro, M.; Lacal-Arántegui, R. Assessing Complementarity of Wind and Solar Resources for Energy Production in Italy. A Monte Carlo Approach. Renew. Energy 2014, 63, 576–586. [CrossRef]14. Miglietta, M.M.; Huld, T.; Monforti-Ferrario, F. 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