Journal
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 60, Issue -, Pages 1206-1212Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2016.01.106
Keywords
Wind power prediction; Numerical weather prediction; Cluster analysis; Modeling; Daily similarity
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The selection of training data for establishing a model directly affects the prediction precision. Wind power has the characteristic of daily similarity. The corresponding meteorological data also has the characteristic of daily similarity. This paper proposes a new model with cluster analysis of the numerical weather prediction information. The similar day with the predicted day is searched as training sample to a generalized regression neural network model. The numerical weather prediction data and actual wind power data from a wind farm are used in this study to test the model. The prediction results show that correct cluster analysis method is a useful tool in day-ahead wind power prediction. (C) 2016 Published by Elsevier Ltd.
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