Advances in computational intelligence for floating offshore wind turbines aerodynamics: Current state review and future potential

H.H. Mian, F.A. Machot, H. Ullah, A. Keprate and M.S. Siddiqui

Renewable and Sustainable Energy Reviews, 2025, vol. 224, issue C

Abstract: Floating offshore wind turbines (FOWTs) are an emerging technology that allows wind energy generation in deep waters. Numerical simulations are pivotal in designing, analyzing, and optimizing FOWTs due to their multiphysics nature. This review presents recent advances in numerical simulation tools, ranging from low-fidelity engineering models to high-fidelity computational fluid dynamics (CFD) codes for FOWT aerodynamics. We review various open-source and commercial software developments and summarize validation projects focused on improving the FOWT simulations. Given the dynamic nature of floating turbines, the impact of wake aerodynamics has also been critically assessed. Additionally, data-driven modeling has emerged as a promising approach for improving FOWT design, leveraging data from numerical models and experiments. We discuss the strengths and limitations of various computational methods, highlighting the potential of integrating data-driven techniques with next-generation AI methods. Finally, future research directions and opportunities in floating wind energy are identified.

Keywords: Floating offshore wind turbine (FOWT); Computational fluid dynamics (CFD); Machine learning; Data-driven; Multi-disciplinary; Aerodynamics (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.rser.2025.116098

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