Missing wind data forecasting with adaptive neuro-fuzzy inference system

Hocaoglu F. O., Oysal Y., Kurban M.

Neural Computing and Applications, cilt.18, sa.3, ss.207-212, 2009 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/s00521-008-0172-8
  • Dergi Adı: Neural Computing and Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.207-212
  • Anahtar Kelimeler: ANFIS, Back-propagation, Forecasting, Missing data, Wind energy, Wind speed
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Hayır

Özet

In any region, to begin generating electricity from wind energy, it is necessary to determine the 1-year distribution characteristics of wind speed. For this aim, a wind observation station must be constructed and 1-year wind speed and direction data must be collected. For determining the distribution characteristics, the collected data must be statistically analyzed. The continuity and reliability of the data are quite important for such studies on the days when possible faults can occur in any part of the observation unit or on days when, the system is on maintenance, it is not possible to record any data. In this study, it is assumed that the station had not worked at some randomly chosen days and that for these days no data could be recorded. The missing data are predicted using the data that were recorded before and after fault or maintenance by an adaptive neuro-fuzzy inference system (ANFIS). It is seen that ANFIS is successful for such a study. © 2008 Springer-Verlag London Limited.