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AuthorQuevedo, Jarrizon
AuthorHerrera Moya, Idalberto
AuthorMariano-Hernández, Deyslen
AuthorSbriz-Zeitun, Giuseppe
AuthorCannone, Carla
AuthorHowells, Mark
AuthorYeganyan, Rudolf
AuthorAybar-Mejía, Miguel
Accessioned date2024-01-24T21:50:37Z
Available date2024-01-24T21:50:37Z
Year2023
CitationQuevedo, J., Moya, I. H., Mariano-Hernández, D., Sbriz-Zeitun, G., Cannone, C., Howells, M., ... & Aybar-Mejía, M. (2023). Techno-economic dataset and assumptions for long-term energy systems modelling in the Dominican Republic (2024-2050). Data in Brief, 110012. Recuperado de:es
URIhttps://bvearmb.do/handle/123456789/3936
AbstractThe land transport sector, impacting fossil fuel consumption, has been selected as one of the sectors to apply decarbonization strategies. Energy systems modelling is an applied tool to evaluate scenarios and strategies that can be implemented in the transport sector to achieve energy transitions. These energy modelling tools need a dataset that allows the simulation of alternative scenarios of the systems. For this purpose, a collection and processing of technical-economic data is needed to ensure a quality input for simulation tools. This article presents a set of open data to create a model of the energy system of the Dominican Republic to assess alternative scenarios and develop strategies to achieve the energy transition in the land transport sector. This exercise is performed to support the energy planning policies of the country. Although the dataset is presented for the conditions of the Dominican Republic, the insight regarding data gathering and processing can be applied to other island countries.es
LanguageEnglishes
PublishedData in Brief, 110012es
Rights© 2023 TheAuthor(s). Published by Elsevier Inc.es
Rights URIhttp://creativecommons.org/licenses/by/4.0/es
SubjectRecursos naturales - República Dominicanaes
SubjectEnergías renovableses
SubjectTecnologíaes
TitleTechno-economic dataset and assumptions for long-term energy systems modelling in the Dominican Republic (2024–2050)es
dc.identifier.doihttps://doi.org/10.1016/j.dib.2023.110012
Material typeArticlees
Type of contentScientific researches
AccessOpenes
AudienceTechnicians, professionals and scientistses


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This is an open access article under the CC BY 4.0 Attribution 4.0 International license.
Access and downloading this document are subject to this license: This is an open access article under the CC BY 4.0 Attribution 4.0 International license.
© 2023 TheAuthor(s). Published by Elsevier Inc.