Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia
This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12 110 N 71 550 W. A wind speed and direction sensor, a barometric pressure sensor, and a...
- Autores:
-
Valencia Ochoa, Guillermo
Núñez Alvarez, José
Vanegas Chamorro, Marley
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7468
- Acceso en línea:
- https://hdl.handle.net/11323/7468
https://doi.org/10.1016/j.dib.2019.104753
https://repositorio.cuc.edu.co/
- Palabra clave:
- Wind speed
Wind probability distribution
Wind direction
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
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| dc.title.spa.fl_str_mv |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| title |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| spellingShingle |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia Wind speed Wind probability distribution Wind direction |
| title_short |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| title_full |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| title_fullStr |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| title_full_unstemmed |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| title_sort |
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia |
| dc.creator.fl_str_mv |
Valencia Ochoa, Guillermo Núñez Alvarez, José Vanegas Chamorro, Marley |
| dc.contributor.author.spa.fl_str_mv |
Valencia Ochoa, Guillermo Núñez Alvarez, José Vanegas Chamorro, Marley |
| dc.subject.spa.fl_str_mv |
Wind speed Wind probability distribution Wind direction |
| topic |
Wind speed Wind probability distribution Wind direction |
| description |
This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12 110 N 71 550 W. A wind speed and direction sensor, a barometric pressure sensor, and a temperature sensor were used to obtain the presented data. These data were taken at the height of 10 m, which is the highest point of the weather station. The data taken by the meteorological station correspond to a period of 20 years (1993e2013), with hourly frequency. For the missing data, a mathematical model to estimate the Julian averages was developed, allowing to calculate the frequency histograms and four types of probability distributions for these data. Also, the representative wind roses were generated, taking into account the averages in each of the 12 months of the year. |
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2019 |
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2019 |
| dc.date.accessioned.none.fl_str_mv |
2020-11-24T16:30:00Z |
| dc.date.available.none.fl_str_mv |
2020-11-24T16:30:00Z |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_6501 |
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Text |
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info:eu-repo/semantics/article |
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http://purl.org/redcol/resource_type/ART |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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acceptedVersion |
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https://hdl.handle.net/11323/7468 |
| dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.dib.2019.104753 |
| dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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https://hdl.handle.net/11323/7468 https://doi.org/10.1016/j.dib.2019.104753 https://repositorio.cuc.edu.co/ |
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Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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spa |
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spa |
| dc.relation.references.spa.fl_str_mv |
[1] M.P. Pinto, J.K. Moreno, Y.A. Munoz, A. Ospino, Technical and economic evaluation of a small-scale wind power system ~ located in berlin, Colombia, Tecciencia 13 (24) (2018) 63e72. [2] A.-L.J. Luis, An approximation to the probability normal distribution and its inverse, Ing. Invest. Tecnol. 16 (4) (Oct. 2015) 605e611. [3] M. Ordaz, A simple approximation to the Gaussian distribution, Struct. Saf. 9 (4) (Jun. 1991) 315e318. [4] K. Krishnamoorthy, Handbook of the Normal Distribution Distributions with Applications, University of Louisiana Lafayette, 2010. [5] P.-A. Amaya-Martínez, A.-J. Saavedra-Montes, E.-I. Arango-Zuluaga, A statistical analysis of wind speed distribution models in the Aburr a Valley, Colombia, CT&F - Ciencia, Tecnol. y Futur. 5 (5) (2018) 121e136. [6] J.A. Carta, P. Ramírez, Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions, Renew. Energy 32 (3) (Mar. 2007) 518e531. [7] H. Bidaoui, I. El Abbassi, A. El Bouardi, A. Darcherif, Wind speed data analysis using Weibull and Rayleigh distribution functions, case study: five cities northern Morocco, Procedia Manuf. 32 (Jan. 2019) 786e793. |
| dc.rights.spa.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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Corporación Universidad de la Costa |
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Data in Brief |
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Corporación Universidad de la Costa |
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Valencia Ochoa, GuillermoNúñez Alvarez, JoséVanegas Chamorro, Marley2020-11-24T16:30:00Z2020-11-24T16:30:00Z2019https://hdl.handle.net/11323/7468https://doi.org/10.1016/j.dib.2019.104753Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12 110 N 71 550 W. A wind speed and direction sensor, a barometric pressure sensor, and a temperature sensor were used to obtain the presented data. These data were taken at the height of 10 m, which is the highest point of the weather station. The data taken by the meteorological station correspond to a period of 20 years (1993e2013), with hourly frequency. For the missing data, a mathematical model to estimate the Julian averages was developed, allowing to calculate the frequency histograms and four types of probability distributions for these data. Also, the representative wind roses were generated, taking into account the averages in each of the 12 months of the year.Valencia Ochoa, GuillermoNúñez Alvarez, JoséVanegas Chamorro, Marleyapplication/pdfspaCorporación Universidad de la CostaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Data in Briefhttps://www.sciencedirect.com/science/article/pii/S2352340919311084?via%3DihubWind speedWind probability distributionWind directionData set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - ColombiaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] M.P. Pinto, J.K. Moreno, Y.A. Munoz, A. Ospino, Technical and economic evaluation of a small-scale wind power system ~ located in berlin, Colombia, Tecciencia 13 (24) (2018) 63e72.[2] A.-L.J. Luis, An approximation to the probability normal distribution and its inverse, Ing. Invest. Tecnol. 16 (4) (Oct. 2015) 605e611.[3] M. Ordaz, A simple approximation to the Gaussian distribution, Struct. Saf. 9 (4) (Jun. 1991) 315e318.[4] K. Krishnamoorthy, Handbook of the Normal Distribution Distributions with Applications, University of Louisiana Lafayette, 2010.[5] P.-A. Amaya-Martínez, A.-J. Saavedra-Montes, E.-I. Arango-Zuluaga, A statistical analysis of wind speed distribution models in the Aburr a Valley, Colombia, CT&F - Ciencia, Tecnol. y Futur. 5 (5) (2018) 121e136.[6] J.A. Carta, P. Ramírez, Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions, Renew. Energy 32 (3) (Mar. 2007) 518e531.[7] H. Bidaoui, I. El Abbassi, A. El Bouardi, A. Darcherif, Wind speed data analysis using Weibull and Rayleigh distribution functions, case study: five cities northern Morocco, Procedia Manuf. 32 (Jan. 2019) 786e793.PublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.cuc.edu.co/bitstreams/675c8ddd-a781-4df4-81bb-0b15881cb786/download4460e5956bc1d1639be9ae6146a50347MD52ORIGINALData set on wind speed, wind direction and wind.pdfData set on wind speed, wind direction and wind.pdfapplication/pdf2826090https://repositorio.cuc.edu.co/bitstreams/52ef3f0d-60fe-4921-8d5c-01f70879fec6/download40417d59a656375bfda38f793b398c5eMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/3a098b04-59eb-4b64-8cdc-077343986196/downloade30e9215131d99561d40d6b0abbe9badMD53THUMBNAILData set on wind speed, wind direction and wind.pdf.jpgData set on wind speed, wind direction and 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