Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 123, Issue -, Pages 362-371Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2016.06.053
Keywords
Wind energy; Wind power; Wind energy forecasting
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Funding
- Scientific and Technological Research Council of Turkey (TUBITAK) [213M549]
- 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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