Advancing Wind Energy Efficiency: A Systematic Review of Aerodynamic Optimization in Wind Turbine Blade Design

Ali Akbar Firoozi, Farzad Hejazi () and Ali Asghar Firoozi
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Ali Akbar Firoozi: Department of Civil Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone UB0061, Botswana
Farzad Hejazi: School of Engineering, University of the West of England, Bristol BS16 1QY, UK
Ali Asghar Firoozi: Department of Civil Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone UB0061, Botswana

Energies, 2024, vol. 17, issue 12, 1-30

Abstract: Amid rising global demand for sustainable energy, wind energy emerges as a crucial renewable resource, with the aerodynamic optimization of wind turbine blades playing a key role in enhancing energy efficiency. This systematic review scrutinizes recent advancements in blade aerodynamics, focusing on the integration of cutting-edge aerodynamic profiles, variable pitch and twist technologies, and innovative materials. It extensively explores the impact of Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI) on blade design enhancements, illustrating their significant contributions to aerodynamic efficiency improvements. By reviewing research from the last decade, this paper provides a comprehensive overview of current trends, addresses ongoing challenges, and suggests potential future developments in wind turbine blade optimization. Aimed at researchers, engineers, and policymakers, this review serves as a crucial resource, guiding further innovations and aligning with global renewable energy objectives. Ultimately, this work seeks to facilitate technological advancements that enhance the efficiency and viability of wind energy solutions.

Keywords: aerodynamic optimization; wind turbine blades; Computational Fluid Dynamics (CFD); renewable energy; material innovation; artificial intelligence in energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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