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Review of computer-aided numerical simulation in wind energy

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  • Miller, Aaron
  • Chang, Byungik
  • Issa, Roy
  • Chen, Gerald

Abstract

Many advances have been made during the last decade in the development and application of computational fluid dynamics (CFD), finite element analysis (FEA), numerical weather modeling, and other numerical methods as applied to the wind energy industry. The current information about this area of study may help researchers gage research efforts. Specifically, micro-siting, wind modeling and prediction, blade optimization and modeling, high resolution turbine flow modeling, support structure analysis, and noise prediction have been the main focuses of recent research. The advances in this area of research are enabling better designs and greater efficiencies than were possible previously. The trends toward system coupling, parallel computing, and replacing experiments are discussed. The shortcomings of recent research and areas of possible future research are also presented.

Suggested Citation

  • Miller, Aaron & Chang, Byungik & Issa, Roy & Chen, Gerald, 2013. "Review of computer-aided numerical simulation in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 122-134.
    • Handle: RePEc:eee:rensus:v:25:y:2013:i:c:p:122-134
    DOI: 10.1016/j.rser.2013.03.059
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    3. Engeland, Kolbjørn & Borga, Marco & Creutin, Jean-Dominique & François, Baptiste & Ramos, Maria-Helena & Vidal, Jean-Philippe, 2017. "Space-time variability of climate variables and intermittent renewable electricity production – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 600-617.
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    5. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    6. Benitz, M.A. & Lackner, M.A. & Schmidt, D.P., 2015. "Hydrodynamics of offshore structures with specific focus on wind energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 692-716.
    7. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    8. Siddiqui, M. Salman & Rasheed, Adil & Tabib, Mandar & Kvamsdal, Trond, 2019. "Numerical investigation of modeling frameworks and geometric approximations on NREL 5 MW wind turbine," Renewable Energy, Elsevier, vol. 132(C), pages 1058-1075.
    9. Cheng, Xu & Yan, Bowen & Zhou, Xuhong & Yang, Qingshan & Huang, Guoqing & Su, Yanwen & Yang, Wei & Jiang, Yan, 2024. "Wind resource assessment at mountainous wind farm: Fusion of RANS and vertical multi-point on-site measured wind field data," Applied Energy, Elsevier, vol. 363(C).
    10. Bendjebbas, H. & Abdellah-ElHadj, A. & Abbas, M., 2016. "Full-scale, wind tunnel and CFD analysis methods of wind loads on heliostats: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 452-472.
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    12. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.

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