The analysis of time-varying high-order moment of wind power time series

Abstract

The efficient wind power forecasting is of great significance for the safety and stability of power grid. Analysis on the high order moment of wind power time series play an important role in improving the forecasting accuracy of wind power. With the rolling subsample generalized auto-regressive conditional heteroskedasticity with skewness and kurtosis (GARCHSK) model sequence, the analysis method for conditional skewness and conditional kurtosis of wind power time series is proposed. The dynamic curves of parameter are presented by estimating the characteristic parameters in the subsample models. Moreover, the time-varying structure of high order moment of the wind power time series is analyzed. A Generalized News Impact Curve (GNIC) is proposed, and the impact of news on the conditional skewness and conditional kurtosis are measured and evaluated by the third order GNIC and the fourth order GNIC. The result of case based on the wind power data of Jiangsu power grid demonstrates that the time-varying structure of high-order moments of wind power time series is steady relatively, and the time-varying characteristics of high-order moments are further verified by GNIC.