Optimal design of Archimedes Wind Turbine using genetic algorithm

Omid Salah Samiani and Mehrdad Boroushaki

Energy, 2025, vol. 314, issue C

Abstract: This study aims to employ Genetic Algorithms (GA) to optimize the Archimedes Wind Turbine's (AWT) structure. The distinct design of the AWT necessitates a different methodology than standard lift-type wind turbines. Computational Fluid Dynamics (CFD) was used to evaluate the performance of the design based on the SST k-ω model. In order to validate the simulation results, the acquired data was compared with those from earlier design studies. Simulation results showed that the differences between the two studies' Mean Absolute Error (MAE) were only 5.9 %. GA was selected in an iterative link with ANSYS software to find the optimal turbine's structure. This study investigated several scenarios in which the design variables including opening angle, pitches, and rotational speed were changed, either separately or in combination. In the most comprehensive scenario, an optimized AWT with opening angle of 63.49°, Tip Speed Ratio (TSR) of 1.12, pitch1 value of 115.03 mm, and pitch2 value of 389.54 mm was obtained, where the search space includes all parameters. This design resulted in a power coefficient equal to 0.2644, which shows a 27.72 % increase in efficiency and 7.94 % reduce in thrust force.

Keywords: Wind energy; Archimedes wind turbine; Computational fluid dynamics; Genetic algorithms; Optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:314:y:2025:i:c:s0360544224039355

DOI: 10.1016/j.energy.2024.134157

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