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Multi-kalman filter to wind power forecasting

dc.contributor.authorSalgado, Paulo
dc.contributor.authorIgrejas, Getúlio
dc.contributor.authorAfonso, Paulo Alexandre Ferreira
dc.date.accessioned2020-04-27T09:21:16Z
dc.date.available2020-04-27T09:21:16Z
dc.date.issued2018
dc.description.abstractWind power forecasting methods are important for the safety of wind renewable energy utilization. However, because wind power is weather dependent and, thus, can be variable and intermittent over different time-scales, it’s difficult to build accurate and robust predictive models. In this context, an accurate model is a relevant contribution for a reliable large-scale wind power integration. This paper explores a new approach using a multi-model Kalman filter to provide an estimate of the average hourly wind speed, in a 24 hours horizon. The K-means algorithm is used to obtain the characteristics curves of wind speed each time the sub-model is used for forecasting. The accuracy of the proposed forecasting model is compared with other statistical methods, namely some that are usually considered suitable, robust and accurate.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSalgado, Paulo; Igrejas, Getúlio; Afonso, Paulo (2018). Multi-kalman filter to wind power forecasting. In 2018 13th APCA International Conference on Automatic Control and Soft Computing (CONTROLO). Ponta Delgada, Portugalpt_PT
dc.identifier.doi10.1109/CONTROLO.2018.8514268pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/21820
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleMulti-kalman filter to wind power forecastingpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlacePonta Delgada, Portugalpt_PT
oaire.citation.endPage114pt_PT
oaire.citation.startPage110pt_PT
oaire.citation.title2018 13th APCA International Conference on Automatic Control and Soft Computing (CONTROLO)pt_PT
person.familyNameIgrejas
person.givenNameGetúlio
person.identifier.orcid0000-0002-6820-8858
person.identifier.ridM-8571-2013
person.identifier.scopus-author-id47761255900
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isAuthorOfPublication.latestForDiscoveryab4092ec-d1b1-4fe0-b65a-efba1310fd5a

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