Prediction of wind power generation based on time series wavelet transform for large Wind Farm

The development of wind generation has rapidly progressed over the last decade, the most important application for wind power prediction is to reduce the need for balancing energy and reserve power, which are needed to integrate wind power into the balancing of supply and demand in the electricity supply system. This paper presents a new method of wind power prediction in short-term with Artificial Neural Network (ANN) prediction model based on wavelet transform of chaotic time series. The data from the wind farm located in the Fujin Wind Farm of China are used for this study. The results reported in this paper show that the new method based on wavelet neural networks has better prediction properties than its similar back-propagation networks for prediction of wind power generation.