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Experimental study on wind speeds in a complex-terrain wind farm and analysis of wake effects

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

Abstract

In this paper, wind speed deficits have been quantified based on the field observations from the hilly Shiren wind farm in China. Two lidars have been applied to measure wind speeds in the wind farm. Two clusters of wind turbines in different layout patterns were chosen for the experiments. One cluster was the upstream-and-downstream pattern, which was used to investigate the upstream turbine’s wake impact on the downstream turbine. According to the experiment, the wake width of the downstream turbine widened and the largest wind speed deficit decreased gradually in the downstream direction. Meanwhile, the wake centerlines of upstream and downstream wind turbines were subjected to the wind direction and may not be in the same line. The other cluster was the side-by-side pattern, which was to investigate how the wakes and the wake interactions develop downwind of a row of wind turbines. It has been found that huge wind speed deficits existed behind the wind turbines. The wind speeds reduced mostly from 14.4 m/s to 8.0 m/s in the downwind direction and from 12.4 m/s to 4.2 m/s in the crosswind direction. Wind speeds were not stable in the far-wake zone. The wake boundary was not easy to determine as well. When wakes of two adjacent turbines encountering, the interaction effect became complicated. In these experiments, the complex terrain is one of the most important factors that complicates the wake distribution. Therefore, the influence of the terrain shape on wake distribution should be continuously investigated in the future.

Suggested Citation

  • Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2020. "Experimental study on wind speeds in a complex-terrain wind farm and analysis of wake effects," Applied Energy, Elsevier, vol. 272(C).
  • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920307273
    DOI: 10.1016/j.apenergy.2020.115215
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    References listed on IDEAS

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    1. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    2. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    3. Kim, Soo-Hyun & Shin, Hyung-Ki & Joo, Young-Chul & Kim, Keon-Hoon, 2015. "A study of the wake effects on the wind characteristics and fatigue loads for the turbines in a wind farm," Renewable Energy, Elsevier, vol. 74(C), pages 536-543.
    4. Gao, Xiaoxia & Li, Bingbing & Wang, Tengyuan & Sun, Haiying & Yang, Hongxing & Li, Yonghua & Wang, Yu & Zhao, Fei, 2020. "Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements," Applied Energy, Elsevier, vol. 260(C).
    5. Yang, Xiaolei & Pakula, Maggie & Sotiropoulos, Fotis, 2018. "Large-eddy simulation of a utility-scale wind farm in complex terrain," Applied Energy, Elsevier, vol. 229(C), pages 767-777.
    6. Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2019. "Validations of three-dimensional wake models with the wind field measurements in complex terrain," Energy, Elsevier, vol. 189(C).
    7. Gao, Xiaoxia & Wang, Tengyuan & Li, Bingbing & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Zhao, Fei, 2019. "Investigation of wind turbine performance coupling wake and topography effects based on LiDAR measurements and SCADA data," Applied Energy, Elsevier, vol. 255(C).
    8. Sun, Haiying & Yang, Hongxing, 2018. "Study on an innovative three-dimensional wind turbine wake model," Applied Energy, Elsevier, vol. 226(C), pages 483-493.
    9. Sun, Haiying & Yang, Hongxing & Gao, Xiaoxia, 2019. "Investigation into spacing restriction and layout optimization of wind farm with multiple types of wind turbines," Energy, Elsevier, vol. 168(C), pages 637-650.
    10. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Hiromori, Yuto, 2018. "Investigation of wake characteristic of a 30 kW rated power Horizontal Axis Wind Turbine with wake model and field measurement," Applied Energy, Elsevier, vol. 225(C), pages 1190-1204.
    11. Sun, Haiying & Yang, Hongxing, 2020. "Numerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake model," Renewable Energy, Elsevier, vol. 147(P1), pages 192-203.
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    6. Radünz, William Corrêa & de Almeida, Everton & Gutiérrez, Alejandro & Acevedo, Otávio Costa & Sakagami, Yoshiaki & Petry, Adriane Prisco & Passos, Júlio César, 2022. "Nocturnal jets over wind farms in complex terrain," Applied Energy, Elsevier, vol. 314(C).
    7. Pacheco de Sá Sarmiento, Franciene Izis & Goes Oliveira, Jorge Luiz & Passos, Júlio César, 2022. "Impact of atmospheric stability, wake effect and topography on power production at complex-terrain wind farm," Energy, Elsevier, vol. 239(PC).
    8. 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).
    9. He, Ruiyang & Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2022. "Wind tunnel tests for wind turbines: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
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