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Experimental study on wake interactions and performance of the turbines with different rotor-diameters in adjacent area of large-scale wind farm

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  • Fei, Zhao
  • Tengyuan, Wang
  • Xiaoxia, Gao
  • Haiying, Sun
  • Hongxing, Yang
  • Zhonghe, Han
  • Yu, Wang
  • Xiaoxun, Zhu

Abstract

Caused by the expansion construction of large-scale wind farm, wind turbines of different rotor-diameters always exist in typical area with abundant wind resources. This paper investigates the wake characteristics of turbines with different rotor-diameters and their wake interactions as well as performance through LiDAR measurement and SCADA data. The experiment wind farm is located in North China with a flat terrain and three different types of wind turbines are installed. Results show that the wake recovery is related to the rotor diameter, the larger of the turbine, the slower of its wake recovery. The wake of downwind turbine is aggravated by the upstream turbine’s wake, reflected in broader wake width, larger velocity deficit and depth. Meanwhile, the upstream wind turbine’s wake that close to the downstream wind turbine can also be affected, reflected in the velocity deficit and the wake width suddenly increases when the wake approaching the downwind turbine. The power loss caused by wake effect increased sharply when wind speed decreases and the wake of a 1.5 MW wind turbine makes a great power loss even after a long distance, thus, the wake effect of large wind turbine should be paid more attentions.

Suggested Citation

  • Fei, Zhao & Tengyuan, Wang & Xiaoxia, Gao & Haiying, Sun & Hongxing, Yang & Zhonghe, Han & Yu, Wang & Xiaoxun, Zhu, 2020. "Experimental study on wake interactions and performance of the turbines with different rotor-diameters in adjacent area of large-scale wind farm," Energy, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:energy:v:199:y:2020:i:c:s0360544220305235
    DOI: 10.1016/j.energy.2020.117416
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    1. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (Part I: Power performance)," Energy, Elsevier, vol. 113(C), pages 713-722.
    2. Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.
    3. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake characteristics of a Horizontal Axis Wind Turbine in vertical axis direction with field experiments," Energy, Elsevier, vol. 141(C), pages 262-272.
    4. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    5. Song, MengXuan & Wu, BingHeng & Chen, Kai & Zhang, Xing & Wang, Jun, 2016. "Simulating the wake flow effect of wind turbines on velocity and turbulence using particle random walk method," Energy, Elsevier, vol. 116(P1), pages 583-591.
    6. Shaler, Kelsey & Kecskemety, Krista M. & McNamara, Jack J., 2019. "Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions," Renewable Energy, Elsevier, vol. 136(C), pages 607-620.
    7. Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
    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, 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.
    10. 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).
    11. Li, Qing’an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake effects on a Horizontal Axis Wind Turbine in field experiments (Part I: Horizontal axis direction)," Energy, Elsevier, vol. 134(C), pages 482-492.
    12. Peng, H.Y. & Lam, H.F., 2016. "Turbulence effects on the wake characteristics and aerodynamic performance of a straight-bladed vertical axis wind turbine by wind tunnel tests and large eddy simulations," Energy, Elsevier, vol. 109(C), pages 557-568.
    13. Torres Garcia, E. & Aubrun, S. & Coupiac, O. & Girard, N. & Boquet, M., 2019. "Statistical characteristics of interacting wind turbine wakes from a 7-month LiDAR measurement campaign," Renewable Energy, Elsevier, vol. 130(C), pages 1-11.
    14. 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).
    15. Chen, Jian & Pan, Xiong & Wang, Canxing & Hu, Guojun & Xu, Hongtao & Liu, Pengwei, 2019. "Airfoil parameterization evaluation based on a modified PARASEC method for a H-Darrious rotor," Energy, Elsevier, vol. 187(C).
    16. Lopez, Daniel & Kuo, Jim & Li, Ni, 2019. "A novel wake model for yawed wind turbines," Energy, Elsevier, vol. 178(C), pages 158-167.
    17. Baba-Ahmadi, Mohammad H. & Dong, Ping, 2017. "Numerical simulations of wake characteristics of a horizontal axis tidal stream turbine using actuator line model," Renewable Energy, Elsevier, vol. 113(C), pages 669-678.
    18. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
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    7. Xiaoxia, Gao & Luqing, Li & Shaohai, Zhang & Xiaoxun, Zhu & Haiying, Sun & Hongxing, Yang & Yu, Wang & Hao, Lu, 2022. "LiDAR-based observation and derivation of large-scale wind turbine's wake expansion model downstream of a hill," Energy, Elsevier, vol. 259(C).
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    10. 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.
    11. 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.
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