Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS
Planning for offshore wind energy projects is intricate due to the consideration of multiple variables in identifying optimal project areas. The primary challenge lies in locating suitable sites, a process that often necessitates extensive feasibility studies spanning several years. The primary goal...
- Autores:
-
Ospino Castro, Adalberto
Ospino C., Adalberto
Robles Algarín, Carlos
Hernández Callejo, Luis
Muñoz Maldonado, Yecid
Mangones Cordero, Amanda
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13986
- Acceso en línea:
- https://hdl.handle.net/11323/13986
https://repositorio.cuc.edu.co/
- Palabra clave:
- Fuzzy Analytic Hierarchy Process (FAHP)
Geographic Information System (GIS)
Multi-Criteria Decision-Making (MCDM)
Offshore wind projects
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)
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| dc.title.eng.fl_str_mv |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| title |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| spellingShingle |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS Fuzzy Analytic Hierarchy Process (FAHP) Geographic Information System (GIS) Multi-Criteria Decision-Making (MCDM) Offshore wind projects |
| title_short |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| title_full |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| title_fullStr |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| title_full_unstemmed |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| title_sort |
Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GIS |
| dc.creator.fl_str_mv |
Ospino Castro, Adalberto Ospino C., Adalberto Robles Algarín, Carlos Hernández Callejo, Luis Muñoz Maldonado, Yecid Mangones Cordero, Amanda |
| dc.contributor.author.none.fl_str_mv |
Ospino Castro, Adalberto Ospino C., Adalberto Robles Algarín, Carlos Hernández Callejo, Luis Muñoz Maldonado, Yecid Mangones Cordero, Amanda |
| dc.contributor.editor.none.fl_str_mv |
Cavallaro, Fausto |
| dc.subject.proposal.eng.fl_str_mv |
Fuzzy Analytic Hierarchy Process (FAHP) Geographic Information System (GIS) Multi-Criteria Decision-Making (MCDM) Offshore wind projects |
| topic |
Fuzzy Analytic Hierarchy Process (FAHP) Geographic Information System (GIS) Multi-Criteria Decision-Making (MCDM) Offshore wind projects |
| description |
Planning for offshore wind energy projects is intricate due to the consideration of multiple variables in identifying optimal project areas. The primary challenge lies in locating suitable sites, a process that often necessitates extensive feasibility studies spanning several years. The primary goal of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize criteria and sub-criteria, facilitating decision-making in choosing appropriate locations for offshore wind projects in the Colombian Caribbean Sea. The weights derived from FAHP were utilized in a Geographic Information System (GIS) to analyze the physical characteristics of the Caribbean Sea’s surface. This tool plays a critical role in evaluating and selecting sites that fulfill established criteria, providing a database of indicators and map visualizations. Four criteria were defined: technical, environmental, social, and economic, along with fourteen sub-criteria, which were prioritized through FAHP based on expert judgment. The results revealed that the most relevant sub-criteria were protected areas and wind speed. Utilizing the ArcGIS Pro software, five zones meeting the predetermined criteria were identified, defining the most feasible areas for offshore wind farm installation, located in the departments of Guajira, Magdalena, Atlántico and Bolívar. The GIS–FAHP methods proved to be useful for feasibility analysis. |
| publishDate |
2023 |
| dc.date.issued.none.fl_str_mv |
2023-12-06 |
| dc.date.accessioned.none.fl_str_mv |
2025-02-26T17:10:34Z |
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2025-02-26T17:10:34Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Castro, A.O.; Robles-Algarín, C.; Hernández-Callejo, L.; Muñoz Maldonado, Y.; Cordero, A.M. Feasibility Analysis of Offshore Wind Power Projects in the Caribbean Region of Colombia: A Case Study Using FAHP–GIS. Sustainability 2023, 15, 16620. https://doi.org/10.3390/su152416620 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/11323/13986 |
| dc.identifier.doi.none.fl_str_mv |
10.3390/su152416620 |
| dc.identifier.eissn.none.fl_str_mv |
2071-1050 |
| dc.identifier.instname.none.fl_str_mv |
Corporación Universidad de la Costa |
| dc.identifier.repourl.none.fl_str_mv |
https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
Castro, A.O.; Robles-Algarín, C.; Hernández-Callejo, L.; Muñoz Maldonado, Y.; Cordero, A.M. Feasibility Analysis of Offshore Wind Power Projects in the Caribbean Region of Colombia: A Case Study Using FAHP–GIS. Sustainability 2023, 15, 16620. https://doi.org/10.3390/su152416620 10.3390/su152416620 2071-1050 Corporación Universidad de la Costa |
| url |
https://hdl.handle.net/11323/13986 https://repositorio.cuc.edu.co/ |
| dc.language.iso.none.fl_str_mv |
eng |
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eng |
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Sustainability |
| dc.relation.references.none.fl_str_mv |
Sadigov, R. Rapid growth of the world population and its socioeconomic results. Sci. World J. 2022, 8, 8110229 Thellufsen, J.Z.; Lund, H.; Sorknæs, P.; Østergaard, P.A.; Chang, M.; Drysdale, D.; Nielsen, S.; Djørup, S.R.; Sperling, K. Smart energy cities in a 100% renewable energy context. Renew. Sustain. Energy Rev. 2020, 129, 109922 Yarashynskaya, A.; Prus, P. Smart Energy for a Smart City: A Review of Polish Urban Development Plans. Energies 2022, 15, 8676 Chenic, A.Ș.; Cretu, A.I.; Burlacu, A.; Moroianu, N.; Vîrjan, D.; Huru, D.; Stanef-Puica, M.R.; Enachescu, V. Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint. Sustainability 2022, 14, 8622 Breton, S.P.; Moe, G. Status, Plans and Technologies for Offshore Wind Turbines in Europe and North America. Renew. Energy 2009, 34, 646–654 Vasileiou, M.; Loukogeorgaki, E.; Vagiona, D.G. GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece. Renew. Sustain. Energy Rev. 2017, 73, 745–757 Willsteed, E.A.; Jude, S.; Gill, A.B.; Birchenough, S.N.R. Obligations and aspirations: A critical evaluation of offshore wind farm cumulative impact assessments. Renew. Sustain. Energy Rev. 2018, 82, 2332–2345 Mahdy, M.; Bahaj, A.S. Multi criteria decision analysis for offshore wind energy potential in Egypt. Renew. Energy 2018, 118, 278–289 Nezhad, M.M.; Neshat, M.; Groppi, D.; Marzialetti, P.; Heydari, A.; Sylaios, G.; Garcia, D.A. A primary offshore wind farm site assessment using reanalysis data: A case study for Samothraki island. Renew. Energy 2021, 172, 667–679 Wu, B.; Yip, T.L.; Xie, L.; Wang, Y. A fuzzy-MADM based approach for site selection of offshore wind farm in busy waterways in China. Ocean Eng. 2018, 168, 121–132 Villacreses, G.; Gaona, G.; Martínez-Gómez, J.; Jijón, D.J. Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renew. Energy 2017, 109, 275–286 Vinhoza, A.; Schaeffer, R. Brazil’s offshore wind energy potential assessment based on a Spatial Multi-Criteria Decision Analysis. Renew. Sustain. Energy Rev. 2021, 146, 111185 Ziemba, P. Uncertain Multi-Criteria analysis of offshore wind farms projects investments–case study of the Polish Economic Zone of the Baltic Sea. Appl. Energy 2022, 309, 118232 Pires, A.L.G.; Rotella-Junior, P.; Morioka, S.N.; Rocha, L.C.S.; Bolis, I. Main trends and criteria adopted in economic feasibility studies of offshore wind energy: A Systematic Literature Review. Energies 2021, 15, 12 Zalhaf, A.S.; Elboshy, B.; Kotb, K.M.; Han, Y.; Almaliki, A.H.; Aly, R.M.H.; Elkadeem, M.R. A High-Resolution Wind Farms Suitability Mapping Using GIS and Fuzzy AHP Approach: A National-Level Case Study in Sudan. Sustainability 2022, 14, 358 Ayodele, T.R.; Ogunjuyigbe, A.S.O.; Odigie, O.; Munda, J.L. A Multi-criteria GIS Based Model for Wind Farm Site Selection Using Interval Type-2 Fuzzy Analytic Hierarchy Process: The Case Study of Nigeria. Appl. Energy 2018, 228, 1853–1869 Wang, Y.; Xu, L.; Solangi, Y.A. Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustain. Cities Soc. 2020, 52, 101861 Sapkota, K.; Shabbiruddin; Sherpa, K. S. Wind farm site suitability assessment & validation using geospatially explicit multi-criteria approach: A case study of South Sikkim, India. Int. J. Green Energy 2023, 20, 1–28 Costoya, X.; de Castro, M.; Santos, F.; Sousa, M.C.; Gómez-Gesteira, M. Projections of Wind Energy Resources in the Caribbean for the 21st century. Energy 2019, 178, 356–367 Rueda-Bayona, J.G.; Guzmán, A.; Eras, J.J.C.; Silva-Casarín, R.; Bastidas-Arteaga, E.; Horrillo-Caraballo, J. Renewables energies in Colombia and the opportunity for the offshore wind technology. J. Clean. Prod. 2019, 220, 529–543 |
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© 2023 by the authors. |
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Atribución 4.0 Internacional (CC BY 4.0) |
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https://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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19 páginas |
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application/pdf |
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Región Caribe Colombiana |
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Multidisciplinary Digital Publishing Institute (MDPI) |
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Switzerland |
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Multidisciplinary Digital Publishing Institute (MDPI) |
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Atribución 4.0 Internacional (CC BY 4.0)© 2023 by the authors.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ospino Castro, AdalbertoOspino C., Adalbertovirtual::864-1Robles Algarín, CarlosHernández Callejo, LuisMuñoz Maldonado, YecidMangones Cordero, AmandaCavallaro, Fausto2025-02-26T17:10:34Z2025-02-26T17:10:34Z2023-12-06Castro, A.O.; Robles-Algarín, C.; Hernández-Callejo, L.; Muñoz Maldonado, Y.; Cordero, A.M. Feasibility Analysis of Offshore Wind Power Projects in the Caribbean Region of Colombia: A Case Study Using FAHP–GIS. Sustainability 2023, 15, 16620. https://doi.org/10.3390/su152416620https://hdl.handle.net/11323/1398610.3390/su1524166202071-1050Corporación Universidad de la Costahttps://repositorio.cuc.edu.co/Planning for offshore wind energy projects is intricate due to the consideration of multiple variables in identifying optimal project areas. The primary challenge lies in locating suitable sites, a process that often necessitates extensive feasibility studies spanning several years. The primary goal of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize criteria and sub-criteria, facilitating decision-making in choosing appropriate locations for offshore wind projects in the Colombian Caribbean Sea. The weights derived from FAHP were utilized in a Geographic Information System (GIS) to analyze the physical characteristics of the Caribbean Sea’s surface. This tool plays a critical role in evaluating and selecting sites that fulfill established criteria, providing a database of indicators and map visualizations. Four criteria were defined: technical, environmental, social, and economic, along with fourteen sub-criteria, which were prioritized through FAHP based on expert judgment. The results revealed that the most relevant sub-criteria were protected areas and wind speed. Utilizing the ArcGIS Pro software, five zones meeting the predetermined criteria were identified, defining the most feasible areas for offshore wind farm installation, located in the departments of Guajira, Magdalena, Atlántico and Bolívar. The GIS–FAHP methods proved to be useful for feasibility analysis.19 páginasapplication/pdfengMultidisciplinary Digital Publishing Institute (MDPI)Switzerlandhttps://www.mdpi.com/2071-1050/15/24/16620Feasibility analysis of offshore wind power projects in the Caribbean Region of Colombia: a case study using FAHP–GISArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Región Caribe ColombianaSustainabilitySadigov, R. Rapid growth of the world population and its socioeconomic results. Sci. World J. 2022, 8, 8110229Thellufsen, J.Z.; Lund, H.; Sorknæs, P.; Østergaard, P.A.; Chang, M.; Drysdale, D.; Nielsen, S.; Djørup, S.R.; Sperling, K. Smart energy cities in a 100% renewable energy context. Renew. Sustain. Energy Rev. 2020, 129, 109922Yarashynskaya, A.; Prus, P. Smart Energy for a Smart City: A Review of Polish Urban Development Plans. Energies 2022, 15, 8676Chenic, A.Ș.; Cretu, A.I.; Burlacu, A.; Moroianu, N.; Vîrjan, D.; Huru, D.; Stanef-Puica, M.R.; Enachescu, V. Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint. Sustainability 2022, 14, 8622Breton, S.P.; Moe, G. Status, Plans and Technologies for Offshore Wind Turbines in Europe and North America. Renew. Energy 2009, 34, 646–654Vasileiou, M.; Loukogeorgaki, E.; Vagiona, D.G. GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece. Renew. Sustain. Energy Rev. 2017, 73, 745–757Willsteed, E.A.; Jude, S.; Gill, A.B.; Birchenough, S.N.R. Obligations and aspirations: A critical evaluation of offshore wind farm cumulative impact assessments. Renew. Sustain. Energy Rev. 2018, 82, 2332–2345Mahdy, M.; Bahaj, A.S. Multi criteria decision analysis for offshore wind energy potential in Egypt. Renew. Energy 2018, 118, 278–289Nezhad, M.M.; Neshat, M.; Groppi, D.; Marzialetti, P.; Heydari, A.; Sylaios, G.; Garcia, D.A. A primary offshore wind farm site assessment using reanalysis data: A case study for Samothraki island. Renew. Energy 2021, 172, 667–679Wu, B.; Yip, T.L.; Xie, L.; Wang, Y. A fuzzy-MADM based approach for site selection of offshore wind farm in busy waterways in China. Ocean Eng. 2018, 168, 121–132Villacreses, G.; Gaona, G.; Martínez-Gómez, J.; Jijón, D.J. Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renew. Energy 2017, 109, 275–286Vinhoza, A.; Schaeffer, R. Brazil’s offshore wind energy potential assessment based on a Spatial Multi-Criteria Decision Analysis. Renew. Sustain. Energy Rev. 2021, 146, 111185Ziemba, P. Uncertain Multi-Criteria analysis of offshore wind farms projects investments–case study of the Polish Economic Zone of the Baltic Sea. Appl. Energy 2022, 309, 118232Pires, A.L.G.; Rotella-Junior, P.; Morioka, S.N.; Rocha, L.C.S.; Bolis, I. Main trends and criteria adopted in economic feasibility studies of offshore wind energy: A Systematic Literature Review. Energies 2021, 15, 12Zalhaf, A.S.; Elboshy, B.; Kotb, K.M.; Han, Y.; Almaliki, A.H.; Aly, R.M.H.; Elkadeem, M.R. A High-Resolution Wind Farms Suitability Mapping Using GIS and Fuzzy AHP Approach: A National-Level Case Study in Sudan. Sustainability 2022, 14, 358Ayodele, T.R.; Ogunjuyigbe, A.S.O.; Odigie, O.; Munda, J.L. A Multi-criteria GIS Based Model for Wind Farm Site Selection Using Interval Type-2 Fuzzy Analytic Hierarchy Process: The Case Study of Nigeria. Appl. Energy 2018, 228, 1853–1869Wang, Y.; Xu, L.; Solangi, Y.A. Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustain. Cities Soc. 2020, 52, 101861Sapkota, K.; Shabbiruddin; Sherpa, K. S. Wind farm site suitability assessment & validation using geospatially explicit multi-criteria approach: A case study of South Sikkim, India. Int. J. Green Energy 2023, 20, 1–28Costoya, X.; de Castro, M.; Santos, F.; Sousa, M.C.; Gómez-Gesteira, M. Projections of Wind Energy Resources in the Caribbean for the 21st century. Energy 2019, 178, 356–367Rueda-Bayona, J.G.; Guzmán, A.; Eras, J.J.C.; Silva-Casarín, R.; Bastidas-Arteaga, E.; Horrillo-Caraballo, J. Renewables energies in Colombia and the opportunity for the offshore wind technology. J. Clean. 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>
 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