| Abstract: | 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. |
