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AuthorPereyra-Mariñez, Carlos
AuthorAndrickson-Mora, José
AuthorOcaña-Guevera, Víctor Samuel
AuthorSantos García, Félix
AuthorVallejo Díaz, Alexander
Accessioned date2023-05-04T00:00:37Z
Available date2023-05-04T00:00:37Z
Year2023
CitationPereyra-Maríñez, C., Andrickson-Mora, J., Ocaña-Guevera, V. S., Santos García, F., & Vallejo Díaz, A. (2023). Energy supply systems predicting model for the integration of long-term energy planning variables with sustainable livelihoods approach in remote communities. Energies, 16(7), 3143. Recuperado de:es
URIhttps://bvearmb.do/handle/123456789/2730
AbstractThe Sustainable Development Goals (SDGs) of the United Nations Organization pursue the provision of affordable and quality energy for all human beings, which is why the correct planning of Energy Supply Systems (ESS) in communities that present levels of energy poverty, that is, the impossibility to satisfy their minimum needs for energy services. This work proposes a methodology to evaluate the contribution to development by the adequate provision of the demand of ESS in remote communities through the approach of Sustainable Livelihoods (SLs). The methodology starts from the initial evaluation of the sustainable livelihoods or capitals of the communities and the analysis of their interaction.es
LanguageEnglishes
PublishedEnergies, 16(7), 3143es
Rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland.es
Rights URIhttps://creativecommons.org/licenses/by/4.0/es
SubjectRecursos naturales - República Dominicanaes
SubjectDesarrollo sosteniblees
SubjectEnergías renovableses
SubjectComunidades ruraleses
TitleEnergy supply systems predicting model for the integration of long-term energy planning variables with sustainable livelihoods approach in remote communitieses
dc.identifier.doihttps://doi.org/10.3390/en16073143
Material typeArticlees
Type of contentScientific researches
AccessOpenes
AudienceTechnicians, professionals and scientistses


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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Access and downloading this document are subject to this license: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
© 2023 by the authors. Licensee MDPI, Basel, Switzerland.