Study on Medium-Term and Short-Term Wind Power Forecasting Methods
In the paper, the wind power prediction is devided into medium-term forecasts and short-term forecasts. For medium-term forecasts, we use the weighted moving average method and BP neural network forecasting model, while for short-term forecasts, the ARMA model and combination forecasting model based on the maximum entropy principle are used. The application example shows that the weighted moving average method is easy and can precisely obtain the fluctuation trend of the wind power, while the accuracy rate of the BP neural network forecasting model is 91.23%, which is better than the former. The predictive results of the ARMA model are similar with actual trends and its accuracy rate is 88.98%. The combination model integrates the advantages of the BP neural network and ARMA model, and its accuracy rate is up to 92.58%.