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The Second China Energy Scientist Forum (CESF 2010 E-BOOK)

Xuzhou,China,10.18-10.19，2010

ISBN: 978-1-935068-37-2 Scientific Research Publishing, USA

E-Book 2244pp Pub. Date: October 2010

Category: Medicine & Healthcare

Price: $360

Title: Wind Speed Prediction Based on RBF Neural Network
Source: The Second China Energy Scientist Forum (CESF 2010 E-BOOK) (pp 731-734)
Author(s): Shoudao Huang, College of electrical and information engineering, Hunan university, Changsha, China, 410082
Lang Dai, College of electrical and information engineering, Hunan university, Changsha, China, 410082
Keyuan Huang, College of electrical and information engineering, Hunan university, Changsha, China, 410082
Sheng Ye, College of electrical and information engineering, Hunan university, Changsha, China, 410082
Abstract: Wind speed forecasting is very important to wind farms and power system operation. By use of radial basis function (RBF) neural network the short-term wind speed forecasting is researched. On the premise of without taking into account numerical weather prediction data, with wind speed sequences is used as the input variable, the model was constructed based on the nonlinear approach ability of radial basis function neural networks that was used for the short-term wind speed prediction. Using the model, we have achieved 1h ahead forecasting of the wind speed and its prediction error analysis. The results show that neural network structure and the selection of input sample have a certain impact on the prediction results. The forecasting accuracy of the method is better than BP network.
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