Wind power forecasting based on wavelet neural network and particle swarm optimization

In recent years, wind power generation has been the most promising renewable energy generation mode because it has many satisfying merits. In this paper, a model based on wavelet neural network and particle swarm optimization is proposed to forecast wind power. This paper firstly predicts wind speed, and then obtains wind power through the wind speed-power curve. In the end, the validity and performance of the proposed method is validated via experiment with real data from a wind farm.