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Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements

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Listed:
  • Gao, Xiaoxia
  • Chen, Yao
  • Xu, Shinai
  • Gao, Wei
  • Zhu, Xiaoxun
  • Sun, Haiying
  • Yang, Hongxing
  • Han, Zhonghe
  • Wang, Yu
  • Lu, Hao

Abstract

Large-scale turbines’ wake expansion is influenced both by atmospheric conditions and terrain effects. This paper conducted comparative experimental measurements on the wind turbines’ wake in three wind farms areas of different terrain complexities using Doppler Light Detection and Ranging (LiDARs). Three wind farm areas of different terrain complexities in North China were selected and wake expansions were detected by three LiDARs over a six-month measurement period. Three wake interaction conditions of separate, full, and half wakes were discussed separately in the aforementioned three wind farm areas of different terrain complexities with a total of nine different cases. The velocity deficit (VD) exhibited a complex expression with the terrain complexity increases. In separate wake condition, the VD trend of flat terrain was gentle, and the decline slopes in moderate and complex areas were 0.1243 and 0.0082 respectively. Results also showed that the wake width (WW) became wider as the terrain complexity increases, and the more complex the terrain was, the faster the WW changes. In separate wake, upstream of full and half wake, WWs in moderate and complex areas showed the same growth trend with an increase rate of 87.5%, which was twice as much as that in flat terrain. Results of this study can provide guidance for the micro-siting arrangement and control strategies of wind turbines in wind farms with different terrain complexities.

Suggested Citation

  • Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
  • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014537
    DOI: 10.1016/j.apenergy.2021.118182
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    as
    1. Kruyt, Bert & Lehning, Michael & Kahl, Annelen, 2017. "Potential contributions of wind power to a stable and highly renewable Swiss power supply," Applied Energy, Elsevier, vol. 192(C), pages 1-11.
    2. 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).
    3. 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.
    4. 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.
    5. Mingdi You & Eunshin Byon & Jionghua (Judy) Jin & Giwhyun Lee, 2017. "When wind travels through turbines: A new statistical approach for characterizing heterogeneous wake effects in multi-turbine wind farms," IISE Transactions, Taylor & Francis Journals, vol. 49(1), pages 84-95, January.
    6. 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).
    7. Brogna, Roberto & Feng, Ju & Sørensen, Jens Nørkær & Shen, Wen Zhong & Porté-Agel, Fernando, 2020. "A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain," Applied Energy, Elsevier, vol. 259(C).
    8. 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).
    9. Syed, Abdul Haseeb & Javed, Adeel & Asim Feroz, Raja M. & Calhoun, Ronald, 2020. "Partial repowering analysis of a wind farm by turbine hub height variation to mitigate neighboring wind farm wake interference using mesoscale simulations," Applied Energy, Elsevier, vol. 268(C).
    10. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2020. "Optimal design of wind farms in complex terrains using computational fluid dynamics and adjoint methods," Applied Energy, Elsevier, vol. 261(C).
    11. Castellani, Francesco & Vignaroli, Andrea, 2013. "An application of the actuator disc model for wind turbine wakes calculations," Applied Energy, Elsevier, vol. 101(C), pages 432-440.
    12. Yan, Shu & Shi, Shaoping & Chen, Xinming & Wang, Xiaodong & Mao, Linzhi & Liu, Xiaojie, 2018. "Numerical simulations of flow interactions between steep hill terrain and large scale wind turbine," Energy, Elsevier, vol. 151(C), pages 740-747.
    13. Takanori Uchida, 2020. "Effects of Inflow Shear on Wake Characteristics of Wind-Turbines over Flat Terrain," Energies, MDPI, vol. 13(14), pages 1-31, July.
    14. Xue, Zhanpu & Wang, Wei & Fang, Liqing & Zhou, Jingbo, 2020. "Numerical simulation on structural dynamics of 5 MW wind turbine," Renewable Energy, Elsevier, vol. 162(C), pages 222-233.
    15. 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.
    16. Khan, Mehtab Ahmad & Javed, Adeel & Shakir, Sehar & Syed, Abdul Haseeb, 2021. "Optimization of a wind farm by coupled actuator disk and mesoscale models to mitigate neighboring wind farm wake interference from repowering perspective," Applied Energy, Elsevier, vol. 298(C).
    17. 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).
    18. 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.
    19. Shah Rukh Abbas & Syed Ali Abbas Kazmi & Muhammad Naqvi & Adeel Javed & Salman Raza Naqvi & Kafait Ullah & Tauseef-ur-Rehman Khan & Dong Ryeol Shin, 2020. "Impact Analysis of Large-Scale Wind Farms Integration in Weak Transmission Grid from Technical Perspectives," Energies, MDPI, vol. 13(20), pages 1-32, October.
    20. Radünz, William Corrêa & Sakagami, Yoshiaki & Haas, Reinaldo & Petry, Adriane Prisco & Passos, Júlio César & Miqueletti, Mayara & Dias, Eduardo, 2021. "Influence of atmospheric stability on wind farm performance in complex terrain," Applied Energy, Elsevier, vol. 282(PA).
    21. Castellani, Francesco & Astolfi, Davide & Sdringola, Paolo & Proietti, Stefania & Terzi, Ludovico, 2017. "Analyzing wind turbine directional behavior: SCADA data mining techniques for efficiency and power assessment," Applied Energy, Elsevier, vol. 185(P2), pages 1076-1086.
    22. Hoon Hwangbo & Andrew L. Johnson & Yu Ding, 2018. "Spline model for wake effect analysis: Characteristics of a single wake and its impacts on wind turbine power generation," IISE Transactions, Taylor & Francis Journals, vol. 50(2), pages 112-125, February.
    23. Kuo, Jim Y.J. & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2016. "Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming," Applied Energy, Elsevier, vol. 178(C), pages 404-414.
    24. Barthelmie, R.J. & Pryor, S.C., 2013. "An overview of data for wake model evaluation in the Virtual Wakes Laboratory," Applied Energy, Elsevier, vol. 104(C), pages 834-844.
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