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Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems

The data describe supplementary materials supporting the research article entitled “Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Köppen-Geiger climates” (Mazzeo et al., 2020). Hybrid renewable energy syst...

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Autores principales: Mazzeo, Domenico, Baglivo, Cristina, Matera, Nicoletta, De Luca, Pierangelo, Congedo, Paolo Maria, Oliveti, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666328/
https://www.ncbi.nlm.nih.gov/pubmed/33225026
http://dx.doi.org/10.1016/j.dib.2020.106476
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author Mazzeo, Domenico
Baglivo, Cristina
Matera, Nicoletta
De Luca, Pierangelo
Congedo, Paolo Maria
Oliveti, Giuseppe
author_facet Mazzeo, Domenico
Baglivo, Cristina
Matera, Nicoletta
De Luca, Pierangelo
Congedo, Paolo Maria
Oliveti, Giuseppe
author_sort Mazzeo, Domenico
collection PubMed
description The data describe supplementary materials supporting the research article entitled “Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Köppen-Geiger climates” (Mazzeo et al., 2020). Hybrid renewable energy systems are increasingly adopted worldwide as technically and economically effective solutions to achieve energy decarbonization and greenhouse gas reduction targets. This data article includes the results of worldwide techno-economic optimization of stand-alone and grid-connected photovoltaic-wind hybrid renewable energy systems designed to meet the electrical energy needs of an office district. The technical simulations have been performed in TRNSYS 17 (Transient Energy System) environment. A total of 48 different locations around the world have been chosen across Köppen-Geiger climates with different latitudes and homogeneously distributed over the whole globe, considering very different climates. The analyses have been conducted for 343 different system power configurations, considering both stand-alone and grid-connected systems. A total of 16464 dynamic simulations were performed, summarized in yearly energy output from each component and in energy and economic indicators.
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spelling pubmed-76663282020-11-20 Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems Mazzeo, Domenico Baglivo, Cristina Matera, Nicoletta De Luca, Pierangelo Congedo, Paolo Maria Oliveti, Giuseppe Data Brief Data Article The data describe supplementary materials supporting the research article entitled “Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Köppen-Geiger climates” (Mazzeo et al., 2020). Hybrid renewable energy systems are increasingly adopted worldwide as technically and economically effective solutions to achieve energy decarbonization and greenhouse gas reduction targets. This data article includes the results of worldwide techno-economic optimization of stand-alone and grid-connected photovoltaic-wind hybrid renewable energy systems designed to meet the electrical energy needs of an office district. The technical simulations have been performed in TRNSYS 17 (Transient Energy System) environment. A total of 48 different locations around the world have been chosen across Köppen-Geiger climates with different latitudes and homogeneously distributed over the whole globe, considering very different climates. The analyses have been conducted for 343 different system power configurations, considering both stand-alone and grid-connected systems. A total of 16464 dynamic simulations were performed, summarized in yearly energy output from each component and in energy and economic indicators. Elsevier 2020-11-01 /pmc/articles/PMC7666328/ /pubmed/33225026 http://dx.doi.org/10.1016/j.dib.2020.106476 Text en © 2020 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 Data Article
Mazzeo, Domenico
Baglivo, Cristina
Matera, Nicoletta
De Luca, Pierangelo
Congedo, Paolo Maria
Oliveti, Giuseppe
Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title_full Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title_fullStr Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title_full_unstemmed Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title_short Energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
title_sort energy and economic dataset of the worldwide optimal photovoltaic-wind hybrid renewable energy systems
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666328/
https://www.ncbi.nlm.nih.gov/pubmed/33225026
http://dx.doi.org/10.1016/j.dib.2020.106476
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