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dc.contributor.authorUlazia, Alain
dc.contributor.authorIbarra-Berastegi, Gabriel
dc.contributor.authorSáenz, Jon
dc.contributor.authorCarreno-Madinabeitia, Sheila
dc.contributor.authorGonzález-Rojí, Santos J.
dc.date.accessioned2019-07-23T11:05:50Z
dc.date.available2019-07-23T11:05:50Z
dc.date.issued2019
dc.identifier.citationUlazia, Alain, Gabriel Ibarra-Berastegi, Jon Sáenz, Sheila Carreno-Madinabeitia, and Santos J. González-Rojí. “Seasonal Correction of Offshore Wind Energy Potential Due to Air Density: Case of the Iberian Peninsula.” Sustainability 11, no. 13 (July 2, 2019): 3648. doi:10.3390/su11133648.en
dc.identifier.issn2071-1050en
dc.identifier.urihttp://hdl.handle.net/11556/746
dc.description.abstractA constant value of air density based on its annual average value at a given location is commonly used for the computation of the annual energy production in wind industry. Thus, the correction required in the estimation of daily, monthly or seasonal wind energy production, due to the use of air density, is ordinarily omitted in existing literature. The general method, based on the implementation of the wind speed’s Weibull distribution over the power curve of the turbine, omits it if the power curve is not corrected according to the air density of the site. In this study, the seasonal variation of air density was shown to be highly relevant for the computation of offshore wind energy potential around the Iberian Peninsula. If the temperature, pressure, and moisture are taken into account, the wind power density and turbine capacity factor corrections derived from these variations are also significant. In order to demonstrate this, the advanced Weather Research and Forecasting mesoscale Model (WRF) using data assimilation was executed in the study area to obtain a spatial representation of these corrections. According to the results, the wind power density, estimated by taking into account the air density correction, exhibits a difference of 8% between summer and winter, compared with that estimated without the density correction. This implies that seasonal capacity factor estimation corrections of up to 1% in percentage points are necessary for wind turbines mainly for summer and winter, due to air density changes.en
dc.description.sponsorshipThis work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (AEI/FEDER EU) and the University of the Basque Country (UPV/EHU funded project GIU17/02). The ECMWF ERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server. The authors wish to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for being kind enough to provide data for this study. The computational resources used in the project were provided by I2BASQUE. The authors thank the creators of the WRF/ARW and WRFDA systems for making them freely available to the community. NOAA_OI_SST_V2 data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, through their web-site at http://www.esrl.noaa.gov/psd/ were used in this paper. National Centres for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2008, updated daily. NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format), May 1997—continuing. Research Data Archive at the National Centre for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds337.0/ were used. All the calculations have been carried out in the framework of R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/en
dc.language.isoengen
dc.publisherMDPI AGen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleSeasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsulaen
dc.typearticleen
dc.identifier.doi10.3390/su11133648en
dc.rights.accessRightsopenAccessen
dc.subject.keywordsWeather Research and Forecast Model—WRFen
dc.subject.keywordsData assimilationen
dc.subject.keywordsAir densityen
dc.subject.keywordsOffshore wind energyen
dc.issue.number13en
dc.journal.titleSustainabilityen
dc.page.initial3648en
dc.volume.number11en


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