Current status of wind energy forecasting and a hybrid method for hourly predictions


Okumus İ. , DİNLER A.

ENERGY CONVERSION AND MANAGEMENT, cilt.123, ss.362-371, 2016 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 123
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.enconman.2016.06.053
  • Dergi Adı: ENERGY CONVERSION AND MANAGEMENT
  • Sayfa Sayıları: ss.362-371

Özet

Generating accurate wind energy and/or power forecasts is crucially important for energy trading and planning. The present study initially gives an extensive review of recent advances in statistical wind forecasting. Numerous prediction methods for varying prediction horizons from a few seconds to several months are listed. Then in the light of accurate results in the literature, the present study combines the adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) for 1 h ahead wind speed forecasts. The performance results show the mean absolute percentage errors (MAPE) of 2.2598%, 3.3530% and 3.8589% at three different locations for daily average wind speeds. (C) 2016 Elsevier Ltd. All rights reserved.