4.7 Review

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

Journal

ENERGY CONVERSION AND MANAGEMENT
Volume 123, Issue -, Pages 362-371

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2016.06.053

Keywords

Wind energy; Wind power; Wind energy forecasting

Funding

  1. Scientific and Technological Research Council of Turkey (TUBITAK) [213M549]
  2. Scientific Research Projects Program of Istanbul Medeniyet University [FBA-2013-412]

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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.

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