Predictions of ice formations on wind turbine blades and power production losses due to icing


WIND ENERGY, vol.22, no.7, pp.945-958, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 7
  • Publication Date: 2019
  • Doi Number: 10.1002/we.2333
  • Journal Name: WIND ENERGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.945-958
  • Keywords: atmospheric icing, ice accretion, power losses, wind energy
  • Middle East Technical University Affiliated: Yes


Prediction of ice shapes on a wind turbine blade makes it possible to estimate the power production losses due to icing. Ice accretion on wind turbine blades is responsible for a significant increase in aerodynamic drag and decrease in aerodynamic lift and may even cause premature flow separation. All these events create power losses and the amount of power loss depends on the severity of icing and the turbine blade profile. The role of critical parameters such as wind speed, temperature, liquid water content on the ice shape, and size is analyzed using an ice accretion prediction methodology coupled with a blade element momentum tool. The predicted ice shapes on various airfoil profiles are validated against the available experimental and numerical data in the literature. The error in predicted rime and glime ice volumes and the maximum ice thicknesses varies between 3% and 25% in comparison with the experimental data depending on the ice type. The current study presents an efficient and accurate numerical methodology to perform an investigation for ice-induced power losses under various icing conditions on horizontal axis wind turbines. The novelty of the present work resides in a unified and coupled approach that deals with the ice accretion prediction and performance analysis of iced wind turbines. Sectional ice profiles are first predicted along the blade span, where the concurrence of both rime and glaze ice formations may be observed. The power loss is then evaluated under the varying ice profiles along the blade. It is shown that the tool developed may effectively be used in the prediction of power production losses of wind turbines at representative atmospheric icing conditions.