Uncertainty Quantification of Aerodynamic Icing Losses in Wind Turbine With Polynomial Chaos Expansion

Abstract

Icing of wind turbine blades poses a challenge for the wind power industry in cold climate wind farms. It can lead to production losses of more than 10% of the annual energy production. Knowledge of how the production is affected by icing is of importance. Complicating this reality is the fact that even a small amount of uncertainty in the shape of the accreted ice may result in a large amount of uncertainty in the aerodynamic performance metrics. This paper presents a numerical approach using the technique of polynomial chaos expansion (PCE) to quantify icing uncertainty faster than traditional methods. Time-dependent bi-dimensional Reynolds-averaged Navier–Stokes computational fluid dynamics (RANS-CFD) simulations are considered to evaluate the aerodynamic characteristics at the chosen sample points. The boundary conditions are based on three-dimensional simulations of the rotor. This approach is applied to the NREL 5 MW reference wind turbine allowing to estimate the power loss range due to the leading-edge glaze ice, considering a radial section near the tip. The probability distribution function of the power loss is also assessed. The results of the section are nondimensionalized and assumed valid for the other radial sections. A correlation is found allowing to model the load loss with respect to the glaze ice horn height, as well as the corresponding probability distribution. Considering an equal chance for any of the ice profiles, load loss is estimated to be lower than 6.5% for the entire blade in half of the icing cases, while it could be roughly 4–6 times in the most severe icings.