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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Cerebellar Model Articulation Controller Applied in Short-Term Wind Power Prediction
verfasst von : Yichuan Shao, Xingjia Yao
Erschienen in: Advances in Future Computer and Control Systems
Verlag: Springer Berlin Heidelberg
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Wind Power prediction is very important in the wind power grid management. This paper introduces how to use Cerebellar Model Articulation Controller (CMAC) to build a short-term wind power prediction model.CMAC and Back-propagation Artificial Neural Networks(BP) are used respectively to do the short-term prediction with the data from a wind farm in Inner Mongolia. After comparison of the results, CMAC is more stable, accurate and faster than BP neural network with less training data.. CMAC is considered to be more suitable to do the short-term prediction.