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Three-Dimensional LiDAR Wake Measurements in an Offshore Wind Farm and Comparison with Gaussian and AL Wake Models

Author

Listed:
  • Xin Liu

    (Huaneng Clean Energy Research Institute, Beijing 102209, China)

  • Lailong Li

    (China Huaneng Group, Beijing 100031, China)

  • Shaoping Shi

    (Huaneng Clean Energy Research Institute, Beijing 102209, China)

  • Xinming Chen

    (Huaneng Clean Energy Research Institute, Beijing 102209, China)

  • Songhua Wu

    (College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China)

  • Wenxin Lao

    (Huaneng Clean Energy Research Institute, Beijing 102209, China)

Abstract

Huaneng Rudong 300 MW offshore wind farm project is located in eastern China. The wake effect is one of the major concerns for wind farm operators, as all 70 units are plotted in ranks, and the sea surface roughness is low. This paper investigated the wake intensity by combining a field test and a numerical simulation. To carry out further yaw optimization, a Gaussian wake model was adopted. Firstly, a 3D Light Detection and Ranging device (LiDAR) was used to capture the features in both horizontal and vertical directions of the wake. It indicated that Gaussian wake model can precisely predict the characteristics under time average and steady state in the wind farm. The predicted annual energy production (AEP) of the whole wind farm by the Gaussian model is compared with the calculation result of the actuator line (AL)-based LES method, and the difference between the two methods is mostly under 10%.

Suggested Citation

  • Xin Liu & Lailong Li & Shaoping Shi & Xinming Chen & Songhua Wu & Wenxin Lao, 2021. "Three-Dimensional LiDAR Wake Measurements in an Offshore Wind Farm and Comparison with Gaussian and AL Wake Models," Energies, MDPI, vol. 14(24), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8313-:d:699116
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    References listed on IDEAS

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    4. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2017. "Wind farm layout optimization using a Gaussian-based wake model," Renewable Energy, Elsevier, vol. 107(C), pages 531-541.
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