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dc.contributor.authorUlazia Manterola, Alain ORCID
dc.contributor.authorSáenz Aguirre, Jon ORCID
dc.contributor.authorIbarra Berastegi, Gabriel
dc.contributor.authorGonzález Rojí, Santos José
dc.contributor.authorCarreno Madinabeitia, Sheila
dc.date.accessioned2020-02-28T13:32:25Z
dc.date.available2020-02-28T13:32:25Z
dc.date.issued2019-11-15
dc.identifier.citationEnergy 187 : (2019) // Article ID 115938es_ES
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.urihttp://hdl.handle.net/10810/41858
dc.description.abstractThe literature typically considers constant annual average air density when computing the wind energy potential of a given location. In this work, the recent reanalysis ERA5 is used to obtain global seasonal estimates of wind energy production that include seasonally varying air density. Thus, errors due to the use of a constant air density are quantified. First, seasonal air density changes are studied at the global scale. Then, wind power density errors due to seasonal air density changes are computed. Finally, winter and summer energy production errors due to neglecting the changes in air density are computed by implementing the power curve of the National Renewable Energy Laboratorys 5?MW turbine. Results show relevant deviations for three variables (air density, wind power density, and energy production), mainly in the middle-high latitudes (Hudson Bay, Siberia, Patagonia, Australia, etc.). Locations with variations from -6% to 6% are identified from summers to winters in the Northern Hemisphere. Additionally, simulations with the aeroelastic code FAST for the studied turbine show that instantaneous power production can be affected by greater than 20% below the rated wind speed if a day with realistically high or low air density values is compared for the same turbulent wind speedes_ES
dc.description.sponsorshipThis work was 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-5 data used in this study were obtained from the Copernicus Climate Data Store. All the calculations were carried out in the framework of R Core Team (2016). More can be learnt about R, a language and an environment for statistical computing, at the website of the R Foundation for Statistical Computing, Vienna, Austria (https://www.R-project.org/).es_ES
dc.language.isoenges_ES
dc.publisherPergamon-Elsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/CGL2016-76561-Res_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectwind energy potentiales_ES
dc.subjectair densityes_ES
dc.subjecterases_ES
dc.subjectfluid mechanicses_ES
dc.subjectoffshore windes_ES
dc.subjectdata assimilationes_ES
dc.subjectmesoscale modeles_ES
dc.subjectwrf modeles_ES
dc.subjectsimulationes_ES
dc.subjectsensitivityes_ES
dc.subjectperformancees_ES
dc.subjectareaes_ES
dc.titleGlobal estimations of wind energy potential considering seasonal air density changeses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0360544219316226?via%3Dihub#!es_ES
dc.identifier.doi10.1016/j.energy.2019.115938
dc.departamentoesFísica aplicada IIes_ES
dc.departamentoesIngeniería nuclear y mecánica de fluidoses_ES
dc.departamentoeuFisika aplikatua IIes_ES
dc.departamentoeuIngeniaritza nuklearra eta jariakinen mekanikaes_ES


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2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Except where otherwise noted, this item's license is described as 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)