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dc.contributor.authorAlonso, Joaquín
dc.contributor.authorTernero, Antonio
dc.contributor.authorBatlles, Francisco J.
dc.contributor.authorLópez Rodríguez, Gabriel 
dc.contributor.authorRodríguez, Jorge
dc.contributor.authorBurgaleta, Juan I.
dc.date.accessioned2017-04-24T07:43:03Z
dc.date.available2017-04-24T07:43:03Z
dc.date.issued2014
dc.identifier.citationAlonso, J., Ternero, A., Batlles, F.J., López Rodríguez, G., Rodríguez, J., Burgaleta, J.I.: "Prediction of cloudiness in short time periods using techniques of remote sensing and image processing". Energy Procedia. Vol. 49, págs. 2280-2289, (2014). DOI: 10.1016/j.egypro.2014.03.241en_US
dc.identifier.issn1876-6102
dc.identifier.urihttp://hdl.handle.net/10272/13619
dc.description.abstractIn this work we introduce a methodology which enables to predict the cloudiness in the short and medium termanywhere in the world. Satellite images (Meteosat of Second Generation) are used in combination with images from a sky camera (fisheye lens), showing a ground vision of the clouds, and using the real-time radiation measured on-site as a feedback and as a complement to the cloudiness. The methodology is based on the determination of cloud motion in the images. Obtaining cloud movement vectors from consecutive images, we are able to anticipate the displacement of the previously detected clouds, thus knowing the distribution of clouds in the future. The short-term forecast (less than 1 hour) and the medium-term forecast (up till 3 hours) have a rate of success of 80%. Aiming to have an accurate knowledge of the evolution of cloudiness in the short and medium-term (useful for CSP plant management) an interactive portal has been developed. The application is a user-friendly interface which shows three hours real-time forecasts refreshed each minute, along with useful information for the operation of the CSP plant like the DNI evolution, the original and processed image from satellite MSG-2 as well as that from sky camera. In the application 400 Wm-2 will be considered as the DNI threshold for the optimal operation for a CSP plant. The application has been tested and validated in two different locations: University of Almería (Almería, Spain) and Gemasolar Central Tower Plant (Fuentes de Andalucía, Spain) and it is going to be installed in Valle 1 and 2 Parabolic Trough Plant (San José del Valle, Spain).en_US
dc.description.sponsorshipThis project has been financed by Torresol Energy Investments, S. A., to which we wish to acknowledge their collaboration, and especially to Gemasolar Plant. Also, the authors wish to acknowledge the CDTI (IDI-20091384) and the project (CGL2011-30377-C02-02) that was funded by the Ministerio de Economia y Competitividad.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherForecasten_US
dc.subject.otherCloudinessen_US
dc.subject.otherRemote sensingen_US
dc.subject.otherMeteosat Second Generationen_US
dc.subject.otherSky camerasen_US
dc.titlePrediction of cloudiness in short time periods using techniques of remote sensing and image processingen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.relation.publisherversionhttps://doi.org/10.1016/j.egypro.2014.03.241en_US
dc.identifier.doi10.1016/j.egypro.2014.03.241
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Ministerio de Economia y Competitividad [CGL2011-30377-C02-02]en_US


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