Elsevier

Physics Procedia

Volume 25, 2012, Pages 2304-2308
Physics Procedia

Cerebellar Model Controller Applied in Wind Power Prediction

https://doi.org/10.1016/j.phpro.2012.03.388Get rights and content
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Abstract

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.

Keywords

Neural network
Wind Power prediction
CMAC
BP

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