Wind power chaos prediction based on Volterra adaptive filter

It is significant to forecast short-term generated power of wind farm for the security, stability and economic operation of the power grid with wind farm connected. This paper reconstructs the phase space for the wind generated power time series by using the C-C algorithm, and proves that the wind generated power time series has the chaotic characteristics through calculating the largest Lyapunov index. Different order of Volterra adaptive filters are used to forecast short-time wind generated power. Two different wind farms are used to verify the method, and the analysis results show that the results forecasted by the designed forecasting model can reflect future changes trend of wind generated power and possess high accuracy, while different order of Volterra adaptive filters has different accuracy, the lower the order is, the higher the accuracy is.