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Data from renewable energy assessments for resort islands in the South China Sea
Renewable energy assessments for resort islands in the South China Sea were conducted that involves the collection and analysis of meteorological and topographic data. The meteorological data was used to assess the PV, wind and hydropower system potentials on the islands. Furthermore, the reconnaiss...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4685173/ https://www.ncbi.nlm.nih.gov/pubmed/26779562 http://dx.doi.org/10.1016/j.dib.2015.11.043 |
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author | Basir Khan, M. Reyasudin Jidin, Razali Pasupuleti, Jagadeesh |
author_facet | Basir Khan, M. Reyasudin Jidin, Razali Pasupuleti, Jagadeesh |
author_sort | Basir Khan, M. Reyasudin |
collection | PubMed |
description | Renewable energy assessments for resort islands in the South China Sea were conducted that involves the collection and analysis of meteorological and topographic data. The meteorological data was used to assess the PV, wind and hydropower system potentials on the islands. Furthermore, the reconnaissance study for hydro-potentials were conducted through topographic maps in order to determine the potential sites suitable for development of run-of-river hydropower generation. The stream data was collected for 14 islands in the South China Sea with a total of 51 investigated sites. The data from this study are related to the research article “Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea” published in Energy (Khan et al., 2015) [1]. |
format | Online Article Text |
id | pubmed-4685173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-46851732016-01-15 Data from renewable energy assessments for resort islands in the South China Sea Basir Khan, M. Reyasudin Jidin, Razali Pasupuleti, Jagadeesh Data Brief Data Article Renewable energy assessments for resort islands in the South China Sea were conducted that involves the collection and analysis of meteorological and topographic data. The meteorological data was used to assess the PV, wind and hydropower system potentials on the islands. Furthermore, the reconnaissance study for hydro-potentials were conducted through topographic maps in order to determine the potential sites suitable for development of run-of-river hydropower generation. The stream data was collected for 14 islands in the South China Sea with a total of 51 investigated sites. The data from this study are related to the research article “Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea” published in Energy (Khan et al., 2015) [1]. Elsevier 2015-11-25 /pmc/articles/PMC4685173/ /pubmed/26779562 http://dx.doi.org/10.1016/j.dib.2015.11.043 Text en © 2015 The Authors 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 Basir Khan, M. Reyasudin Jidin, Razali Pasupuleti, Jagadeesh Data from renewable energy assessments for resort islands in the South China Sea |
title | Data from renewable energy assessments for resort islands in the South China Sea |
title_full | Data from renewable energy assessments for resort islands in the South China Sea |
title_fullStr | Data from renewable energy assessments for resort islands in the South China Sea |
title_full_unstemmed | Data from renewable energy assessments for resort islands in the South China Sea |
title_short | Data from renewable energy assessments for resort islands in the South China Sea |
title_sort | data from renewable energy assessments for resort islands in the south china sea |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4685173/ https://www.ncbi.nlm.nih.gov/pubmed/26779562 http://dx.doi.org/10.1016/j.dib.2015.11.043 |
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