A large volume wind data for renewable energy applications

The objective of the collection of dataset is to calculate the wind energy potential in the selected location using large volume of wind dataset. The wind energy potential data were collected at 100 m height from MSL (Mean Sea Level) from 2014 to 2016. The wind speed and direction were used to analy...

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Detalles Bibliográficos
Autores principales: Bharani, R., Sivaprakasam, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Energy
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685692/
https://www.ncbi.nlm.nih.gov/pubmed/31406906
http://dx.doi.org/10.1016/j.dib.2019.104291
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author Bharani, R.
Sivaprakasam, A.
author_facet Bharani, R.
Sivaprakasam, A.
author_sort Bharani, R.
collection PubMed
description The objective of the collection of dataset is to calculate the wind energy potential in the selected location using large volume of wind dataset. The wind energy potential data were collected at 100 m height from MSL (Mean Sea Level) from 2014 to 2016. The wind speed and direction were used to analyse wind energy characteristics and suitable site for wind turbine installation. The maximum wind power density was observed at monitoring sites S1, S2, S3 and S4. The altitude of the monitoring station and geomorphology of the site significantly controls the wind power density.
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spelling pubmed-66856922019-08-12 A large volume wind data for renewable energy applications Bharani, R. Sivaprakasam, A. Data Brief Energy The objective of the collection of dataset is to calculate the wind energy potential in the selected location using large volume of wind dataset. The wind energy potential data were collected at 100 m height from MSL (Mean Sea Level) from 2014 to 2016. The wind speed and direction were used to analyse wind energy characteristics and suitable site for wind turbine installation. The maximum wind power density was observed at monitoring sites S1, S2, S3 and S4. The altitude of the monitoring station and geomorphology of the site significantly controls the wind power density. Elsevier 2019-07-19 /pmc/articles/PMC6685692/ /pubmed/31406906 http://dx.doi.org/10.1016/j.dib.2019.104291 Text en © 2019 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 Energy
Bharani, R.
Sivaprakasam, A.
A large volume wind data for renewable energy applications
title A large volume wind data for renewable energy applications
title_full A large volume wind data for renewable energy applications
title_fullStr A large volume wind data for renewable energy applications
title_full_unstemmed A large volume wind data for renewable energy applications
title_short A large volume wind data for renewable energy applications
title_sort large volume wind data for renewable energy applications
topic Energy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685692/
https://www.ncbi.nlm.nih.gov/pubmed/31406906
http://dx.doi.org/10.1016/j.dib.2019.104291
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AT sivaprakasama alargevolumewinddataforrenewableenergyapplications
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AT sivaprakasama largevolumewinddataforrenewableenergyapplications

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