Investigation of a new analytical wake prediction method for offshore floating wind turbines considering an accurate incoming wind flow

被引:11
|
作者
Wang, Yangwei [1 ]
Lin, Jiahuan [1 ]
Zhang, Jun [1 ]
机构
[1] Fuzhou Univ, Sch Mech Engn & Automat, Fuzhou 350116, Peoples R China
基金
中国国家自然科学基金;
关键词
Offshore floating wind turbine; Incoming wind flow; Wind tunnel measured data; Wake prediction; OPTIMIZATION; TURBULENCE; LOSSES; MODELS;
D O I
10.1016/j.renene.2021.12.060
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
High prediction accuracy of the wake is crucial for the aerodynamic design and layout optimization of the offshore floating wind turbine (OFWT) in a wind farm. In order to achieve this, an innovative threedimensional (3D) analytical wake prediction method is developed for the first time. Compared with previous methods, the present one considers an accurate incoming wind flow including the environmental and structural disturbances, which is more closer to the reality. Besides, it adopts a more physically intuitive wake expansion model and a novel 3D Gaussian wake model to predict the wake. To verify this method, comparisons with the experimental data from four worldwide wind tunnels are conducted. The results are excellent from the near to far wake regions, which can prove its high prediction accuracy. Finally, based on this method, the effects of the included wind disturbances on the wake are analyzed comprehensively to reveal the internal mechanism affecting the prediction. The results show that these wind disturbances can affect the wake significantly. The present study could make a theoretical contribution to the wake modeling and the aerodynamic study of the OFWT.(c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页码:827 / 849
页数:23
相关论文
共 50 条
  • [1] Wind Tunnel Wake Measurements of Floating Offshore Wind Turbines
    Bayati, I.
    Belloli, M.
    Bernini, L.
    Zasso, A.
    [J]. 14TH DEEP SEA OFFSHORE WIND R&D CONFERENCE, EERA DEEPWIND'2017, 2017, 137 : 214 - 222
  • [2] Wake losses optimization of offshore wind farms with moveable floating wind turbines
    Rodrigues, S. F.
    Pinto, R. Teixeira
    Soleimanzadeh, M.
    Bosman, Peter A. N.
    Bauer, P.
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2015, 89 : 933 - 941
  • [3] Development of a free vortex wake method code for offshore floating wind turbines
    Sebastian, T.
    Lackner, M. A.
    [J]. RENEWABLE ENERGY, 2012, 46 : 269 - 275
  • [4] A review of aerodynamic and wake characteristics of floating offshore wind turbines
    Wang, Xinbao
    Cai, Chang
    Cai, Shang-Gui
    Wang, Tengyuan
    Wang, Zekun
    Song, Juanjuan
    Rong, Xiaomin
    Li, Qing'an
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2023, 175
  • [5] Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave
    Zhang, Huanqiang
    Gao, Xiaoxia
    Lu, Hongkun
    Zhao, Qiansheng
    Zhu, Xiaoxun
    Wang, Yu
    Zhao, Fei
    [J]. APPLIED ENERGY, 2024, 365
  • [6] A NEW METHOD FOR THE DESIGN AND COUPLED ANALYSIS OF FLOATING OFFSHORE WIND TURBINES
    Veen, Daniel
    Pahos, Spiro J.
    Meng, Shawn
    Dillenburg, Simon
    [J]. PROCEEDINGS OF ASME 2023 42ND INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE & ARCTIC ENGINEERING, OMAE2023, VOL 8, 2023,
  • [7] WAKE EFFECTS ON MULTILINE ANCHOR LOADS FOR FLOATING OFFSHORE WIND TURBINES
    Balakrishnan, Krishnaveni
    Arwade, Sanjay
    DeGroot, Don
    [J]. PROCEEDINGS OF ASME 2023 5TH INTERNATIONAL OFFSHORE WIND TECHNICAL CONFERENCE, IOWTC2023, 2023,
  • [8] Rapid Estimation Model for Wake Disturbances in Offshore Floating Wind Turbines
    Zhao, Liye
    Gong, Yongxiang
    Li, Zhiqian
    Wang, Jundong
    Xue, Lei
    Xue, Yu
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2024, 12 (04)
  • [9] Wake Influence on Dynamic Load Characteristics of Offshore Floating Wind Turbines
    Jeon, Minu
    Lee, Soogab
    Kim, Taeseong
    Lee, Seunghoon
    [J]. AIAA JOURNAL, 2016, 54 (11) : 3535 - 3545
  • [10] Dynamic and structural performances of offshore floating wind turbines in turbulent wind flow
    Li, Liang
    Liu, Yuanchuan
    Yuan, Zhiming
    Gao, Yan
    [J]. OCEAN ENGINEERING, 2019, 179 : 92 - 103