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A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect

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  • Sun, Haiying
  • Gao, Xiaoxia
  • Yang, Hongxing

Abstract

This paper provides an overview of full-scale wind field measurements of the wind-turbine wake effect and presents the results and experience of performing a new measurement. First, typical onshore wind-farm measurements are reviewed and summarized, followed by a description of the measurements used in offshore wind farms. Then, the measurements obtained for studying isolated wake effects are introduced. Information about the location, equipment, and process used in a number of experiments are described in detail, followed by a discussion of significant results, an economic analysis, and the experimental difficulties encountered. Validation of a wake model has been the main purpose of some studies, which are also reviewed in this paper. Lastly, the results of a new experiment on the wake interaction effect are presented and summarized. The work presented in this paper advances our understanding of the development process and research status of full-scale wind field measurements of the wake effect. Suggestions are also made regarding future measurements.

Suggested Citation

  • Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2020. "A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    • Handle: RePEc:eee:rensus:v:132:y:2020:i:c:s1364032120303336
    DOI: 10.1016/j.rser.2020.110042
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    5. Luo, Zhaohui & Wang, Longyan & Xu, Jian & Wang, Zilu & Yuan, Jianping & Tan, Andy C.C., 2024. "A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements," Energy, Elsevier, vol. 294(C).
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    8. Zhang, Lijun & Li, Ye & Xu, Wenhao & Gao, Zhiteng & Fang, Long & Li, Rongfu & Ding, Boyin & Zhao, Bin & Leng, Jun & He, Fenglan, 2022. "Systematic analysis of performance and cost of two floating offshore wind turbines with significant interactions," Applied Energy, Elsevier, vol. 321(C).
    9. Wen, Jiahao & Zhou, Lei & Zhang, Hongfu, 2023. "Mode interpretation of blade number effects on wake dynamics of small-scale horizontal axis wind turbine," Energy, Elsevier, vol. 263(PA).
    10. Barnes, Andrew & Marshall-Cross, Daniel & Hughes, Ben Richard, 2021. "Towards a standard approach for future Vertical Axis Wind Turbine aerodynamics research and development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    11. 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).
    12. Neunaber, Ingrid & Hölling, Michael & Whale, Jonathan & Peinke, Joachim, 2021. "Comparison of the turbulence in the wakes of an actuator disc and a model wind turbine by higher order statistics: A wind tunnel study," Renewable Energy, Elsevier, vol. 179(C), pages 1650-1662.
    13. Paxis Marques João Roque & Shyama Pada Chowdhury & Zhongjie Huan, 2021. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study," Energies, MDPI, vol. 14(14), pages 1-22, July.
    14. Imre Delgado & Muhammad Fahim, 2020. "Wind Turbine Data Analysis and LSTM-Based Prediction in SCADA System," Energies, MDPI, vol. 14(1), pages 1-21, December.
    15. Sun, Haiying & Qiu, Changyu & Lu, Lin & Gao, Xiaoxia & Chen, Jian & Yang, Hongxing, 2020. "Wind turbine power modelling and optimization using artificial neural network with wind field experimental data," Applied Energy, Elsevier, vol. 280(C).

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