Abstract: During winter cold wave events, wind turbines in alpine mountainous wind farms in a certain province are prone to capacity loss caused by icing, posing significant challenges to grid dispatching and power balance. To address this issue, a regional prediction method for wind turbine capacity loss caused by icing is proposed, which takes into account both meteorological conditions of glaze ice and freezing fog, and introduces a Freezing Meteorological Index(I_FM) to quantitatively describe the external meteorological conditions of wind power ice-covered in the process of winter cold waves. A predictive model is constructed to map I_FM to wind power capacity loss due to icing. Empirical validation is conducted using multiple typical cold wave events. Results show that the proposed method demonstrates high prediction accuracy across several cold wave processes, and the average accuracy reaches 85.44% in the prediction of capacity loss due to icing in the winter of 2024-2025, indicating strong practical value and regional applicability.

Key words: wind turbine icing, prediction of capacity loss, freezing meteorological index