Colak, IlhamiSagiroglu, SerefYesilbudak, MehmetKabalci, ErsanIbrahim Bulbul, H.2024-09-112024-09-112015978-147999982-8https://doi.org/10.1109/ICRERA.2015.7418698https://hdl.handle.net/11363/86124th International Conference on Renewable Energy Research and Applications, ICRERA 2015 -- 22 November 2015 through 25 November 2015 -- Palermo -- 119791This 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.eninfo:eu-repo/semantics/closedAccessforecating; long-term; medium-term; Time series methods; wind power; wind speedConference Object21522010.1109/ICRERA.2015.74186982-s2.0-84964642963N/A