Analytical solution for the cumulative wake of wind turbines in wind farms

被引:56
|
作者
Bastankhah, Majid [1 ]
Welch, Bridget L. [1 ]
Martinez-Tossas, Luis A. [2 ]
King, Jennifer [2 ]
Fleming, Paul [2 ]
机构
[1] Univ Durham, Dept Engn, Durham DH1 3LE, England
[2] Natl Renewable Energy Lab, Natl Wind Technol Ctr, Golden, CO 80401 USA
关键词
wakes; SUBGRID-SCALE MODEL; TURBULENCE CHARACTERISTICS; FLOW; SIMULATIONS; BLOCKAGE; TUNNEL;
D O I
10.1017/jfm.2020.1037
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
This paper solves an approximate form of conservation of mass and momentum for a turbine in a wind farm array. The solution is a fairly simple explicit relationship that predicts the streamwise velocity distribution within a wind farm with an arbitrary layout. As this model is obtained by solving flow-governing equations directly for a turbine that is subject to upwind turbine wakes, no ad hoc superposition technique is needed to predict wind farm flows. A suite of large-eddy simulations (LES) of wind farm arrays is used to examine self-similarity as well as validity of the so-called conservation of momentum deficit for turbine wakes in wind farms. The simulations are performed with and without the presence of some specific turbines in the wind farm. This allows us to systematically study some of the assumptions made to develop the analytical model. A modified version of the conservation of momentum deficit is also proposed to provide slightly better results at short downwind distances, as well as in the far wake of turbines deep inside a wind farm. Model predictions are validated against the LES data for turbines in both full-wake and partial-wake conditions. While our results highlight the limitation in capturing the flow speed-up between adjacent turbine columns, the model is overall able to acceptably predict flow distributions for a moderately sized wind farm. Finally, the paper employs the new model to provide insights on the accuracy of common wake superposition methods.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] Analytical Solution for the Optimal Spacing of Wind Turbines
    Prasad, Ajay K.
    JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME, 2014, 136 (01):
  • [2] Critical evaluation of Wind Turbines' analytical wake models
    Kaldellis, John K.
    Triantafyllou, Panagiotis
    Stinis, Panagiotis
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 144 (144)
  • [3] Optimizing the Distribution of Wind Turbines in Wind Farms
    Durante-Gomez, W.
    Iracheta-Cortez, R.
    Lopez-Molina, F.
    Vidal-Pavon, G.
    Zaragoza-Antonio, S.
    Dorrego-Portela, J. R.
    Torres-Moreno, E.
    2018 IEEE 38TH CENTRAL AMERICA AND PANAMA CONVENTION (CONCAPAN XXXVIII), 2018, : 50 - 56
  • [4] Analysis of wake recovery effects using small-diameter-ratio wind turbines for vertically staggered wind farms
    Yang, Hao
    Chen, Jian
    Zhang, Yu
    Sun, Li
    Li, Chun
    JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2024, 16 (04)
  • [5] Exploring wind farms with alternating two- and three-bladed wind turbines
    Hayat, Imran
    Chatterjee, Tanmoy
    Liu, Huiwen
    Peet, Yulia T.
    Chamorro, Leonardo P.
    RENEWABLE ENERGY, 2019, 138 : 764 - 774
  • [6] Effects of Two-Dimensional Steep Hills on the Performance of Wind Turbines and Wind Farms
    Liu, Luoqin
    Stevens, Richard J. A. M.
    BOUNDARY-LAYER METEOROLOGY, 2020, 176 (02) : 251 - 269
  • [7] Wind farms with counter-rotating wind turbines
    Vasel-Be-Hagh, Ahmadreza
    Archer, Cristina L.
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2017, 24 : 19 - 30
  • [8] Effect of wind turbine nacelle on turbine wake dynamics in large wind farms
    Foti, Daniel
    Yang, Xiaolei
    Shen, Lian
    Sotiropoulos, Fotis
    JOURNAL OF FLUID MECHANICS, 2019, 869 : 1 - 26
  • [9] INVESTIGATION OF TWO ANALYTICAL WAKE MODELS USING DATA FROM WIND FARMS
    Mittal, Anshul
    Taylor, Lafayette K.
    Sreenivas, Kidambi
    Arabshahi, Abdollah
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2011, VOL 6, PTS A AND B, 2012, : 1215 - 1222
  • [10] On the wake deflection of vertical axis wind turbines by pitched blades
    Huang, Ming
    Sciacchitano, Andrea
    Ferreira, Carlos
    WIND ENERGY, 2023, 26 (04) : 365 - 387