Multi-Time Series and -Time Scale Modeling for Wind Speed and Wind Power Forecasting Part II: Medium-Term and Long-Term Applications

Colak I., SAĞIROĞLU Ş., YEŞİLBUDAK M., KABALCI E., BÜLBÜL H. İ.

4th International Conference on Renewable Energy Research and Applications (ICRERA), Palermo, İtalya, 22 - 25 Kasım 2015, ss.215-220 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icrera.2015.7418698
  • Basıldığı Şehir: Palermo
  • Basıldığı Ülke: İtalya
  • Sayfa Sayıları: ss.215-220
  • Anahtar Kelimeler: Time series methods, forecating, medium-term, long-term, wind speed, wind power
  • Gazi Üniversitesi Adresli: Evet

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.