A study of grey theory used in prediction of medium and long-term wind power generation

In this paper, the grey theory is proposed to predict the annual wind power of a wind farm. Considering that wind power generation depends on wind speed, first we may establish wind - power function through the wind power of the pre-installed wind turbine and the corresponding wind speed. And then, bring the daily wind speed data obtained from the National Meteorological Information Center into the wind - power function to obtain the daily wind power. Lastly, we integrate the daily wind power data by an annual cycle, and get the annual wind power. By using the calculated annual wind power, we can establish a grey information renewal GM (1,1) model. Moreover, the model is applied to predict the annual wind power of a wind turbine in Fujin wind farm. We obtain that the normalized average absolute error of the 48 data predicted is 7. 8806%. The predicted result shows that the grey theory for medium and long-term wind power forecasting is feasible.