Data set for the generation of strategies in the selection of renewable energies in Colombia: Evaluation of AHP and FAHP from regional potentials towards a sustainable future

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Electrónica e Computación
dc.contributor.authorMoreno Rocha, Christian Manuel
dc.contributor.authorArenas Buelvas, Daina
dc.contributor.authorVega Machado, Itzjak
dc.contributor.authorPacheco Peña, Juan
dc.date.accessioned2026-04-23T07:38:59Z
dc.date.available2026-04-23T07:38:59Z
dc.date.issued2025
dc.date.updated2026-03-27T12:05:13Z
dc.description.abstractThis analysis examines the evaluation of alternatives using the AHP (Analytic Hierarchy Process) and FAHP (Fuzzy Analytic Hierarchy Process) methodologies in five scenarios (SC1 to SC5), with the aim of comparing the effectiveness of both approaches in incorporating environmental and technical criteria. The findings reveal that, in the SC1 scenario, AHP assigns weights of 14.35 % to A1 and 16.22 % to A2, while FAHP shows a greater dispersion and highlights A6 with 35.22 %. In SC2, AHP favors A1 with 14.16 % and FAHP increases the weight of the environmental criterion to 21.18 %. In SC3, A1 remains the preferred option in both methodologies, although AHP and FAHP exhibit a close weight of 34.00 % and 32.98 %, respectively. In SC4, AHP and FAHP maintain a similar trend, with A1 standing out with 11.12 % and A4 with 34.87 %. Finally, in SC5, the findings show that AHP allocates 8.52 % to A1, while FAHP indicates 10.73 %. The observations suggest that FAHP allows a greater sensitivity to variations in the sub-criteria, thus facilitating a more accurate assessment aligned with sustainability objectives. The relevance of environmental and social criteria across the different scenarios highlights the need to integrate more sustainable approaches into decision-making. It is deduced that, although AHP provides consistent outcomes, FAHP might be more suitable for evaluating alternatives in contexts where complexity and uncertainty are significant. It is recommended to perform sensitivity analysis to delve into the influence of variations in the weights of the criteria on final decisions.en
dc.description.peerreviewedSI
dc.identifier.citationData in Brief Volume 59, April 2025, 111348
dc.identifier.doi10.1016/j.dib.2025.111348
dc.identifier.eissn2352-3409
dc.identifier.essn2352-3409
dc.identifier.urihttps://hdl.handle.net/10347/46925
dc.journal.titleData in Brief
dc.language.isoeng
dc.publisherElsevier
dc.relation.publisherversionhttps://doi.org/10.1016/j.dib.2025.111348
dc.rights© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectApplied mathematics
dc.subjectData handling
dc.subjectDatabase
dc.subjectEnvironmental and energy sustainability
dc.subjectFuzzy logic
dc.subjectSelection of data
dc.titleData set for the generation of strategies in the selection of renewable energies in Colombia: Evaluation of AHP and FAHP from regional potentials towards a sustainable futureen
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication

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