Wind power forecasting is of great significance to the safety

reliability and stability of power grid. In this study

the GARCH type models are employed to explore the asymmetric features of wind power time series and improved forecasting precision. Benchmark Symmetric Curve (BSC) and Asymmetric Curve Index (ACI) are proposed as new asymmetric volatility analytical tool

and several generalized applications are presented. In the case study

the utility of the GARCH-type models in depicting time-varying volatility of wind power time series is demonstrated with the asymmetry effect

verified by the asymmetric parameter estimation. With benefit of the enhanced News Impact Curve (NIC) analysis

the responses in volatility to the magnitude and the sign of shocks are emphasized. The results are all confirmed to be consistent despite varied model specifications. The case study verifies that the models considering the asymmetric effect of volatility benefit the wind power forecasting performance.