Ice accretion prediction on wind turbine blades and aerodynamic shape optimization for minimizing power production losses

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2018
Yırtıcı, Özcan
The global wind energy resources are plentiful in cold climate regions and mountainous areas, which cause ice formation on wind turbine blades. Prediction of ice accretion on wind turbine blades makes it possible to estimate the power losses due to icing. Ice accretion on wind turbine blades is responsible for significant increases in aerodynamic drag and decreases 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 shape. The main objective of this study is to develop a cost-effective and accurate numerical methodology to predict ice accretion on horizontal axis wind turbines and ice-induced power losses under various icing conditions. In addition, a gradient based aerodynamic shape optimization is performed to minimize the power production loss due to ice accretion. The Extended Messinger Model is implemented for the prediction of ice accretion on blade profiles, and the Blade Element Momentum Methodology is implemented for the prediction of power production of clean and iced wind turbines. The role of critical parameters such as wind speed, temperature and liquid water content on ice accretion is studied in detail. The predicted ice shapes on various airfoil profiles are validated against available experimental and numerical data in literature. 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. In the optimization study, the blade profile is modified by using bump functions around the leading edge of the blade profile, and it is shown that the optimized blade profile reduces the power production loss due to icing.

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Citation Formats
Ö. Yırtıcı, “Ice accretion prediction on wind turbine blades and aerodynamic shape optimization for minimizing power production losses,” Ph.D. - Doctoral Program, Middle East Technical University, 2018.