Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm

摘要: It is very important to make accurate forecast of wind power because its indispensable requirement for system stable operation. The research predict by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, evaluate feasibility the predicting power. A description performed. Firstly, a calculation largest Lyapunov exponent time series judgment whether has chaotic behavior are made. Secondly, phase space reconstructed. Finally, prediction model constructed best embedding dimension delay approximate uncertain function which forecasted. And then an optimization weights thresholds conducted algorithm (GA). simulation evaluation effectiveness results show that proposed more accuracy than (BP-ANNs).