Multi-time series and-time scale modeling for wind speed and wind power forecasting part II: Medium-term and long-term applications
Küçük Resim Yok
Tarih
2015
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This 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.
Açıklama
4th International Conference on Renewable Energy Research and Applications, ICRERA 2015 -- 22 November 2015 through 25 November 2015 -- Palermo -- 119791
Anahtar Kelimeler
forecating; long-term; medium-term; Time series methods; wind power; wind speed
Kaynak
2015 International Conference on Renewable Energy Research and Applications, ICRERA 2015
WoS Q Değeri
Scopus Q Değeri
N/A
