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Renewable energy production and demand dataset for the energy system of Colombia
During the last decades, an increasing number of studies have focused their attention on the development of energy system models in order to facilitate sustainable energy planning strategies and understand the technical challenges associated with the integration of renewable energy sources. However,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956762/ https://www.ncbi.nlm.nih.gov/pubmed/31956676 http://dx.doi.org/10.1016/j.dib.2019.105084 |
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author | Pupo-Roncallo, Oscar Campillo, Javier Ingham, Derek Hughes, Kevin Pourkashanian, Mohammed |
author_facet | Pupo-Roncallo, Oscar Campillo, Javier Ingham, Derek Hughes, Kevin Pourkashanian, Mohammed |
author_sort | Pupo-Roncallo, Oscar |
collection | PubMed |
description | During the last decades, an increasing number of studies have focused their attention on the development of energy system models in order to facilitate sustainable energy planning strategies and understand the technical challenges associated with the integration of renewable energy sources. However, these models usually require detailed and large amount of data as inputs. The data presented in this article provides key inputs and modelling assumptions adopted in the research paper titled “Large scale integration of renewable energy sources (RES) in the future Colombian energy system” [1]. These datasets can be used by researchers and policymakers in order to analyse different pathways oriented to the development of low carbon strategies for Colombia and countries with similar energy systems. |
format | Online Article Text |
id | pubmed-6956762 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-69567622020-01-17 Renewable energy production and demand dataset for the energy system of Colombia Pupo-Roncallo, Oscar Campillo, Javier Ingham, Derek Hughes, Kevin Pourkashanian, Mohammed Data Brief Energy During the last decades, an increasing number of studies have focused their attention on the development of energy system models in order to facilitate sustainable energy planning strategies and understand the technical challenges associated with the integration of renewable energy sources. However, these models usually require detailed and large amount of data as inputs. The data presented in this article provides key inputs and modelling assumptions adopted in the research paper titled “Large scale integration of renewable energy sources (RES) in the future Colombian energy system” [1]. These datasets can be used by researchers and policymakers in order to analyse different pathways oriented to the development of low carbon strategies for Colombia and countries with similar energy systems. Elsevier 2020-01-03 /pmc/articles/PMC6956762/ /pubmed/31956676 http://dx.doi.org/10.1016/j.dib.2019.105084 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Energy Pupo-Roncallo, Oscar Campillo, Javier Ingham, Derek Hughes, Kevin Pourkashanian, Mohammed Renewable energy production and demand dataset for the energy system of Colombia |
title | Renewable energy production and demand dataset for the energy system of Colombia |
title_full | Renewable energy production and demand dataset for the energy system of Colombia |
title_fullStr | Renewable energy production and demand dataset for the energy system of Colombia |
title_full_unstemmed | Renewable energy production and demand dataset for the energy system of Colombia |
title_short | Renewable energy production and demand dataset for the energy system of Colombia |
title_sort | renewable energy production and demand dataset for the energy system of colombia |
topic | Energy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956762/ https://www.ncbi.nlm.nih.gov/pubmed/31956676 http://dx.doi.org/10.1016/j.dib.2019.105084 |
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