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

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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)

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.

Suggested Citation

  • Ali Akbar Firoozi & Farzad Hejazi & Ali Asghar Firoozi, 2024. "Advancing Wind Energy Efficiency: A Systematic Review of Aerodynamic Optimization in Wind Turbine Blade Design," Energies, MDPI, vol. 17(12), pages 1-30, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2919-:d:1414389
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    References listed on IDEAS

    as
    1. Lombardi, Lidia & Mendecka, Barbara & Carnevale, Ennio & Stanek, Wojciech, 2018. "Environmental impacts of electricity production of micro wind turbines with vertical axis," Renewable Energy, Elsevier, vol. 128(PB), pages 553-564.
    2. Mishnaevsky, Leon & Hasager, Charlotte Bay & Bak, Christian & Tilg, Anna-Maria & Bech, Jakob I. & Doagou Rad, Saeed & Fæster, Søren, 2021. "Leading edge erosion of wind turbine blades: Understanding, prevention and protection," Renewable Energy, Elsevier, vol. 169(C), pages 953-969.
    3. Cao, Jiu Fa & Zhu, Wei Jun & Shen, Wen Zhong & Sørensen, Jens Nørkær & Sun, Zhen Ye, 2020. "Optimizing wind energy conversion efficiency with respect to noise: A study on multi-criteria wind farm layout design," Renewable Energy, Elsevier, vol. 159(C), pages 468-485.
    4. Jacob R. West & Sanjiva K. Lele, 2020. "Wind Turbine Performance in Very Large Wind Farms: Betz Analysis Revisited," Energies, MDPI, vol. 13(5), pages 1-25, March.
    5. Jensen, J.P. & Skelton, K., 2018. "Wind turbine blade recycling: Experiences, challenges and possibilities in a circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 165-176.
    6. Kevin Leahy & Colm Gallagher & Peter O’Donovan & Dominic T. J. O’Sullivan, 2019. "Issues with Data Quality for Wind Turbine Condition Monitoring and Reliability Analyses," Energies, MDPI, vol. 12(2), pages 1-22, January.
    7. Mahsa Dehghan Manshadi & Majid Ghassemi & Seyed Milad Mousavi & Amir H. Mosavi & Levente Kovacs, 2021. "Predicting the Parameters of Vortex Bladeless Wind Turbine Using Deep Learning Method of Long Short-Term Memory," Energies, MDPI, vol. 14(16), pages 1-17, August.
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