Authors : Aliyu Abubakar; Mutari Hajara Ali

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/m9pmhwjx

Scribd : https://tinyurl.com/mpv9jjje

DOI : https://doi.org/10.38124/ijisrt/26apr929

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This work presents the design of a wind turbine blade airfoil profile tailored for efficient operation in low-windspeed environments. Baseline geometries were selected from low-Reynolds-number airfoils (NACA 2412, NACA 4412, NACA 4418, and NACA 4421). Optimization was carried out using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which systematically adjusted key geometric parameters camber, thickness distribution, leading-edge radius, and trailing-edge angle to enhance aerodynamic efficiency. Candidate airfoils were evaluated in terms of lift coefficient, cross-sectional area, and pressure coefficient distribution, subject to aerodynamic and structural constraints. The optimization process produced a Pareto front of feasible solutions, from which the optimal profile was selected. Results demonstrate that the optimized airfoils provide improved lift-to-drag performance and reduced cut-in wind speeds compared to baseline designs. These findings confirm that targeted aerodynamic optimization can significantly increase energy capture in low-wind-speed regions, thereby broadening the applicability of wind turbines in areas with limited wind resources.

Keywords : Airfoil Optimization, NSGA-II, Lift-to-Drag Ratio, Low Wind Speed, Wind Turbine.

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