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Identification of extreme wind events using a weather type classification

2021-07Journal article Open access
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dc.contributor.authorCouto, António
dc.contributor.authorCosta, Paula Silva
dc.contributor.authorSimões, Teresa
dc.date.accessioned2021-12-30T17:58:37Z
dc.date.available2021-12-30T17:58:37Z
dc.date.issued2021-07
dc.description.abstractABSTRACT: The identification of extreme wind events and their driving forces are crucial to better integrating wind generation into the power system. Recent work related the occurrence of extreme wind events with some weather circulation patterns, enabling the identification of (i) wind power ramps and (ii) low-generation events as well as their intrinsic features, such as the intensity and time duration. Using Portugal as a case study, this work focuses on the application of a weather classification-type methodology to link the weather conditions with wind power generation, namely, the different types of extreme events. A long-term period is used to assess and characterize the changes in the occurrence of extreme weather events and corresponding intensity on wind power production. High variability is expected under cyclonic regimes, whereas low-generation events are most common in anticyclonic regimes. The results of the work provide significant insights regarding wind power production in Portugal, enabling an increase in its predictability.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCouto, António... [et.al.] - Identification of extreme wind events using a weather type classification. In: Energies, 2021, Vol. 14 (13), article nº 3944pt_PT
dc.identifier.doi10.3390/en14133944pt_PT
dc.identifier.eissn1996-1073
dc.identifier.urihttp://hdl.handle.net/10400.9/3653
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationOffshorePlan - POSEUR-01-1001-FC-000007pt_PT
dc.relationSmart-grid optimisation using rate of change of frequency (RoCoF) to rapidly balance power grid network frequency - enabling more widespread use of unpredictable renewables and minimising blackouts
dc.relation.publisherversionhttps://doi.org/10.3390/en14133944pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectEnergypt_PT
dc.subjectWind power systemspt_PT
dc.subjectMeteorologypt_PT
dc.subjectWeather regimespt_PT
dc.subjectVariabilitypt_PT
dc.subjectPower generationpt_PT
dc.titleIdentification of extreme wind events using a weather type classificationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleSmart-grid optimisation using rate of change of frequency (RoCoF) to rapidly balance power grid network frequency - enabling more widespread use of unpredictable renewables and minimising blackouts
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/719137/EU
oaire.citation.issue13pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume14pt_PT
oaire.fundingStreamH2020
person.familyNameCouto
person.familyNameSimões
person.givenNameAntónio
person.givenNameTeresa
person.identifier.ciencia-id2619-80A1-A8AC
person.identifier.ciencia-idF21A-5706-0C78
person.identifier.orcid0000-0002-7368-8817
person.identifier.orcid0000-0003-3325-4085
person.identifier.ridH-7821-2018
person.identifier.scopus-author-id34882158000
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationf164d252-dde5-4894-b948-f35d383ea022
relation.isAuthorOfPublication.latestForDiscoverya0c5b011-98c5-49d3-9ac6-ddfb6027f500
relation.isProjectOfPublication2e72f5fc-094b-441d-9a83-288962ad68b1
relation.isProjectOfPublication.latestForDiscovery2e72f5fc-094b-441d-9a83-288962ad68b1

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