Impact of weather regimes on wind power variability in western Europe

dc.contributor.authorGarrido Pérez, José Manuel
dc.contributor.authorOrdóñez García, Carlos
dc.contributor.authorBarriopedro Cepero, David
dc.contributor.authorGarcía Herrera, Ricardo Francisco
dc.contributor.authorParedes, Daniel
dc.date.accessioned2023-12-04T08:06:01Z
dc.date.available2023-12-04T08:06:01Z
dc.date.issued2020
dc.descriptionEl archivo adjunto es el último manuscrito enviado a la revista antes de ser publicado (posprint).es
dc.description.abstractWe have assessed the dependency of wind power resources in Western Europe on the atmospheric circulation as represented by a new set of 8 tailored weather regimes (WRs). For this purpose, we have derived wind capacity factors (CFs) from a meteorological reanalysis dataset and from high-resolution data simulated by the Weather Research and Forecasting (WRF) model. We first show that WRs capture effectively year-round onshore wind power production variability across Europe, especially over northwestern/central Europe and Iberia. Since the influence of the large-scale circulation on wind energy production is regionally dependent, we have then examined the high-resolution CF data interpolated to the location of more than 100 wind farms in two regions with different orography and climatological features, the United Kingdom and the Iberian Peninsula. The use of the monthly frequencies of occurrence of WRs as predictors in a multi-linear regression model allows explaining up to two thirds of the month-to-month CF variability for most seasons and sub-regions. These results outperform those previously reported based on Euro-Atlantic modes of atmospheric circulation, indicating that the use of WRs customized to the region of study is preferred to reproduce the evolution of wind energy resources. Finally, we have applied these WRs to understand the day-to-day evolution of specific episodes with anomalous regional wind power production. In particular, the wind energy deficit of summer 2018 in the United Kingdom and the surplus of March 2018 in Iberia stemmed from the combination of WRs associated with low and high CFs, respectively. These findings are relevant for the forecast of wind energy resources as the large-scale features of the atmospheric circulation captured by WRs can be modelled with considerably less uncertainty than wind speeds at wind farm sites.en
dc.description.departmentDepto. de Física de la Tierra y Astrofísica
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipIberdrola Renovables Energía S.A.U
dc.description.sponsorshipMinisterio de Educación, Formación Profesional y Deportes (España)
dc.description.sponsorshipMinisterio de Economía, Comercio y Empresa (España)
dc.description.statuspub
dc.identifier.citationJ. M. Garrido-Perez, C. Ordóñez, D. Barriopedro, R. García-Herrera, and D. Paredes, Applied Energy 264, 114731 (2020).
dc.identifier.doi10.1016/j.apenergy.2020.114731
dc.identifier.essn1872-9118
dc.identifier.issn0306-2619
dc.identifier.officialurlhttps://doi.org/10.1016/j.apenergy.2020.114731
dc.identifier.relatedurlhttps://www.sciencedirect.com/science/article/pii/S0306261920302439
dc.identifier.urihttps://hdl.handle.net/20.500.14352/91052
dc.issue.number114731
dc.journal.titleApplied Energy
dc.language.isoeng
dc.page.final12
dc.page.initial1
dc.publisherElsevier
dc.relation.projectIDCGL2017-83198-R
dc.relation.projectIDRTI2018-096402-B-I00
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu551.51
dc.subject.keywordWind power
dc.subject.keywordWeather regimes
dc.subject.keywordAtmospheric circulation
dc.subject.keywordWind resources
dc.subject.keywordWind energy
dc.subject.ucmFísica atmosférica
dc.subject.unesco2501.06 Dinámica Atmosférica
dc.titleImpact of weather regimes on wind power variability in western Europeen
dc.typejournal article
dc.type.hasVersionAM
dc.volume.number264
dspace.entity.typePublication
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relation.isAuthorOfPublication217aa591-37c4-47c8-8763-84aa35c253aa
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