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dc.contributor.authorÇolak, İlhami
dc.contributor.authorSağıroğlu, Şeref
dc.contributor.authorYeşilbudak, Mehmet
dc.contributor.authorKabalcı, Ersan
dc.contributor.authorBülbül, H. İbrahim
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.en_US
dc.publisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USAen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.subjectResearch Subject Categories::TECHNOLOGY::Engineering mechanics::Mechanical and thermal engineering::Mechanical energy engineeringen_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.contributor.departmentİstanbul Gelişim Üniversitesien_US
dc.relation.publicationcategoryKategori Yoken_US

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