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Critical evaluation of Wind Turbines’ analytical wake models

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  • Kaldellis, John K.
  • Triantafyllou, Panagiotis
  • Stinis, Panagiotis

Abstract

The wind energy sector has faced remarkable growth during the last twenty years in view of tackling the global energy consumption rise and the adverse effects of fossil fuels on humans and the environment. On the other hand, the disperse character of wind energy has raised the need for contemporary Wind Turbines (WTs) to be clustered in industrial scale wind parks in an attempt to maximize the exploitation of the prevailing wind energy potential in a specific area. The increased land intensiveness has been considered as the Achille's heel of wind energy. In this context, the thorough wind park micrositing and the subsequent reliable prediction of the wind speed deficit downstream the WTs' rotor, are considered of paramount importance for the optimized WTs' allocation across the examined territory, as they determine the availability for energy extraction.

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  • Kaldellis, John K. & Triantafyllou, Panagiotis & Stinis, Panagiotis, 2021. "Critical evaluation of Wind Turbines’ analytical wake models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:rensus:v:144:y:2021:i:c:s1364032121002835
    DOI: 10.1016/j.rser.2021.110991
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    2. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    3. Sun, Jili & Chen, Zheng & Yu, Hao & Gao, Shan & Wang, Bin & Ying, You & Sun, Yong & Qian, Peng & Zhang, Dahai & Si, Yulin, 2022. "Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines," Renewable Energy, Elsevier, vol. 199(C), pages 71-86.
    4. Liu, Haixiao & Fu, Jianing & Liang, Zetao & Liang, Zhichang & Zhang, Yuming & Xiao, Zhong, 2022. "A simple method of fast evaluating full-field wake velocities for arbitrary wind turbine arrays on complex terrains," Renewable Energy, Elsevier, vol. 201(P1), pages 961-976.
    5. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    6. Purohit, Shantanu & Ng, E.Y.K. & Syed Ahmed Kabir, Ijaz Fazil, 2022. "Evaluation of three potential machine learning algorithms for predicting the velocity and turbulence intensity of a wind turbine wake," Renewable Energy, Elsevier, vol. 184(C), pages 405-420.
    7. Tian, Linlin & Song, Yilei & Xiao, Pengcheng & Zhao, Ning & Shen, Wenzhong & Zhu, Chunling, 2022. "A new three-dimensional analytical model for wind turbine wake turbulence intensity predictions," Renewable Energy, Elsevier, vol. 189(C), pages 762-776.

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