Morphing blade design through airfoil suction surface optimization: enhancing wind turbine energy yield for low wind conditions

This study explores optimization-based strategies for the design of morphing wind turbine blades to adapt to changing wind conditions. The suction surface of the NACA-63418 airfoil is optimized through a Genetic Algorithm, utilizing the ANSYS Design of Experiments toolkit for control of the algorithm’s execution and Fluent solver (ANSYS suite) for evaluation of the objective function. Optimization process was conducted at angles of attack (AoA) of 0° and 8°, under inflow wind speeds of 6 m/s, 8 m/s, and 10 m/s to reflect prevailing wind conditions in South Africa. The resulting optimum geometries differed between the two angles of attack, underscoring the importance of AoA in airfoil optimization. Suction surface modifications yielded improvements in lift-to-drag ratio of 9.6%, 11.1%, and 1.2% at the respective wind speeds. These optimized profiles are subsequently integrated into the design of a three-dimensional rotor using Q-Blade, an open-source Blade Element Momentum Theory code, from which power curves are derived. Morphing schemes are evaluated across wind speed conditions ranging from 4–16 m/s, and performance is benchmarked against a baseline rotor employing the rigid NACA-63418 airfoil. Results demonstrate a 6.9% increase in Annual Energy Production for rotor when morphing airfoil strategies are used, highlighting the potential of optimization-driven morphing blade design to enhance wind turbine power output.