Abstract
Icing is a severe problem faced by wind turbines operating in cold climates. It is affected by various fluctuating parameters. Due to ice accretion, a significant drop in the aerodynamic performance of the blades’ airfoils leads to productivity loss in wind turbines. When ice accretes on airfoils, it leads to a geometry deformation that seriously increases turbulence, particularly on the airfoil suction side at high angles of attack. Modeling and simulation are indispensable tools to estimate the effect of icing on the operation of wind turbines and gain a better understanding of the phenomenon. This paper presents a numerical study to assess the effect of surface roughness distribution, along with the effect of two turbulence models on estimating wind turbine airfoils’ aerodynamic performance losses in the presence of ice. Aerodynamic parameter estimation was performed using ANSYS FLUENT, while ice accretion was simulated using ANSYS FENSAP-ICE. The results using the adopted modeling approaches and the simulation tools were compared with another numerical study and validated against experimental data. The validation process demonstrated the model’s accuracy when considering roughness distribution via the beading model available in ANSYS FENSAP-ICE. The two turbulence models examined (Spalart–Allmaras and k-ω SST) gave comparable results except for the drag at high angles of attack. The k-ω SST model was more efficient in replicating turbulence at high angles of attack, leading to higher accuracy in aerodynamic loss estimation.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference58 articles.
1. Numerical simulation of rime ice on NREL Phase VI blade;J. Wind. Eng. Ind. Aerodyn.,2018
2. Wind turbines ice distribution and load response under icing conditions;Renew. Energy,2017
3. Ice protection systems for wind turbines in cold climate: Characteristics, comparisons and analysis;Renew. Sustain. Energy Rev.,2016
4. Wind turbine ice detection using hyperspectral imaging;Remote Sens. Appl. Soc. Environ.,2022
5. Martini, F., Montoya, L.T.C., and Ilinca, A. (2021). Review of Wind Turbine Icing Modelling Approaches. Energies, 14.
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