Multi-time series and-time scale modeling for wind speed and wind power forecasting part II: Medium-term and long-term applications

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dc.authorscopusid6602990030
dc.authorscopusid7003371572
dc.authorscopusid35792736300
dc.authorscopusid34976617700
dc.authorscopusid57188997543
dc.contributor.authorColak, Ilhami
dc.contributor.authorSagiroglu, Seref
dc.contributor.authorYesilbudak, Mehmet
dc.contributor.authorKabalci, Ersan
dc.contributor.authorIbrahim Bulbul, H.
dc.date.accessioned2024-09-11T19:59:00Z
dc.date.available2024-09-11T19:59:00Z
dc.date.issued2015
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description4th International Conference on Renewable Energy Research and Applications, ICRERA 2015 -- 22 November 2015 through 25 November 2015 -- Palermo -- 119791en_US
dc.description.abstractThis paper represents the second part of an entire study which focuses on multi-time series and-time scale modeling in wind speed and wind power forecasting. In the first part of the entire study [1], firstly, moving average (MA), weighted moving average (WMA), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models are introduced in-depth. Afterwards, the mentioned models are analyzed for very short-term and short-term forecasting scales, comprehensively. In this second part of the entire study, we address the medium-term and long-term prediction performance of MA, WMA, ARMA and ARIMA models in wind speed and wind power forecasting. Particularly, 3-h and 6-h time series forecasting models are constructed in order to carry out 9-h and 24-h ahead forecasting, respectively. Many valuable assessments are made for the employed statistical models in terms of medium-term and long-terms forecasting scales. Finally, many valuable achievements are discussed considering a detailed comparison chart of the entire study. © 2015 IEEE.en_US
dc.identifier.doi10.1109/ICRERA.2015.7418698
dc.identifier.endpage220en_US
dc.identifier.isbn978-147999982-8en_US
dc.identifier.scopus2-s2.0-84964642963en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage215en_US
dc.identifier.urihttps://doi.org/10.1109/ICRERA.2015.7418698
dc.identifier.urihttps://hdl.handle.net/11363/8612
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2015 International Conference on Renewable Energy Research and Applications, ICRERA 2015en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectforecating; long-term; medium-term; Time series methods; wind power; wind speeden_US
dc.titleMulti-time series and-time scale modeling for wind speed and wind power forecasting part II: Medium-term and long-term applicationsen_US
dc.typeConference Objecten_US

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