Adaptive post-processing of short-term wind forecasts for energy applications

DC FieldValueLanguage
dc.contributor.authorSweeney, Conor-
dc.contributor.authorLynch, Peter-
dc.date.accessioned2011-04-08T10:54:04Z-
dc.date.available2011-04-08T10:54:04Z-
dc.date.copyright2010 John Wiley & Sons, Ltd.en
dc.date.issued2011-04-
dc.identifier.citationWind Energyen
dc.identifier.issn1099-1824-
dc.identifier.urihttp://hdl.handle.net/10197/2892-
dc.description.abstractWe present a new method of reducing the error in predicted wind speed, thus enabling better management of wind energy facilities. A numerical weather prediction model, COSMO, was used to produce 48 h forecast data every day in 2008 at horizontal resolutions of 10 and 3 km. A new adaptive statistical method was applied to the model output to improve the forecast skill. The method applied corrective weights to a set of forecasts generated using several post-processing methods. The weights were calculated based on the recent skill of the different forecasts. The resulting forecast data were compared with observed data, and skill scores were calculated to allow comparison between different post-processing methods. The total root mean square error performance of the composite forecast is superior to that of any of the individual methods.en
dc.description.sponsorshipScience Foundation Irelanden
dc.format.extent145967 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherWileyen
dc.rightsThis is the author's version of the following article: "Adaptive postprocessing of short-term wind forecasts for energy applications" (2010) Wind Energy, which has been published in final form at http://www.doi.org/10.1002/we.420en
dc.subjectWind forecastingen
dc.subjectWind energyen
dc.subjectAdaptive filteringen
dc.subjectNWPen
dc.subjectStatistical post-processingen
dc.subject.lcshWind forecastingen
dc.subject.lcshNumerical weather forecastingen
dc.subject.lcshWind poweren
dc.subject.lcshStatistical weather forecastingen
dc.titleAdaptive post-processing of short-term wind forecasts for energy applicationsen
dc.typeJournal Articleen
dc.internal.availabilityFull text availableen
dc.internal.webversionshttp://dx.doi.org/10.1002/we.420-
dc.statusPeer revieweden
dc.identifier.volume14en
dc.identifier.issue3en
dc.identifier.startpage317en
dc.identifier.endpage325en
dc.identifier.doi10.1002/we.420-
dc.neeo.contributorSweeney|Conor|aut|-
dc.neeo.contributorLynch|Peter|aut|-
item.grantfulltextopen-
item.fulltextWith Fulltext-
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