Computing turbulent far-wake development behind a wind turbine with and without swirl

被引:0
|
作者
Hu, Yingying [1 ]
Parameswaran, Siva [1 ]
Tan, Jiannan [1 ]
Dharmarathne, Suranga [1 ]
Marathe, Neha [2 ]
Chen, Zixi [1 ]
Grife, Ronald
Swift, Andrew [2 ]
机构
[1] Texas Tech Univ, Dept Mech Engn, Lubbock, TX 79409 USA
[2] Texas Tech Univ, Wind Sci & Engn Res Ctr, Dept Civil Engn, Lubbock, TX 79409 USA
关键词
far wake; swirl; boundary layer; self-similarity; k-epsilon model; Reynolds Stress transport model; COMPUTATION; ENERGY; FLOW;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Modeling swirling wakes is of considerable interest to wind farm designers. The present work is an attempt to develop a computational tool to understand free, far-wake development behind a single rotating wind turbine. Besides the standard momentum and continuity equations from the boundary layer theory in two dimensions, an additional equation for the conservation of angular momentum is introduced to study axisymmetric swirl effects on wake growth. Turbulence is simulated with two options: the standard k-epsilon model and the Reynolds Stress transport model. A finite volume method is used to discretize the governing equations for mean flow and turbulence quantities. A marching algorithm of expanding grids is employed to enclose the growing far-wake and to solve the equations implicitly at every axial step. Axisymmetric far-wakes with/without swirl are studied at different Reynolds numbers and swirl numbers. Wake characteristics such as wake width, half radius, velocity profiles and pressure profiles are computed. Compared with the results obtained under similar flow conditions using the computational software, FLUENT, this far-wake model shows simplicity with acceptable accuracy, covering large wake regions in far-wake study.
引用
收藏
页码:17 / 26
页数:10
相关论文
共 50 条
  • [41] Characterization of Turbulent Wake of Wind Turbine by Coherent Doppler Lidar
    Wu, Songhua
    Yin, Jiaping
    Liu, Bingyi
    Liu, Jintao
    Li, Rongzhong
    Wang, Xitao
    Feng, Changzhong
    Zhuang, Quanfeng
    Zhang, Kailin
    LIDAR REMOTE SENSING FOR ENVIRONMENTAL MONITORING XIV, 2014, 9262
  • [42] On the homogenization of turbulent flow structures in the wake of a model wind turbine
    Singh, Arvind
    Howard, Kevin B.
    Guala, Michele
    PHYSICS OF FLUIDS, 2014, 26 (02)
  • [43] CHARACTERIZING THE TRANSITIONAL BEHAVIOR OF WIND TURBINE WAKE FROM NEAR TO FAR WAKE REGIMES
    Kumar, Ravi
    Siram, Ojing
    Sahoo, Niranjan
    Saha, Ujjwal K.
    PROCEEDINGS OF THE ASME 2021 POWER CONFERENCE (POWER2021), 2021,
  • [44] Comparative study on the wake deflection behind yawed wind turbine models
    Schottler, Jannik
    Muhle, Franz
    Bartl, Jan
    Peinke, Joachim
    Adaramola, Muyiwa S.
    Saetran, Lars
    Hoelling, Michael
    WAKE CONFERENCE 2017, 2017, 854
  • [45] Wake effect on a uniform flow behind wind-turbine model
    Okulov, V. L.
    Naumov, I. V.
    Mikkelsen, R. F.
    Sorensen, J. N.
    WAKE CONFERENCE 2015, 2015, 625
  • [46] Data-driven modeling of the wake behind a wind turbine array
    Ali, Naseem
    Cal, Raul Bayoan
    JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2020, 12 (03)
  • [47] Experimental investigation of the wake behind a model of wind turbine in a water flume
    Okulov, V. L.
    Naumov, I. N.
    Kabardin, I.
    Mikkelsen, R.
    Sorensen, J. N.
    SCIENCE OF MAKING TORQUE FROM WIND 2012, 2014, 555
  • [48] Reduced-Order Modeling of the Wake Behind a Single Wind Turbine
    Ali, Naseem
    Calaf, Marc
    Cal, Raul Bayoan
    PROGRESS IN TURBULENCE VIII, 2019, 226 : 285 - 290
  • [49] FIELD STUDY OF THE WAKE BEHIND A 2 MW WIND TURBINE.
    Hogstrom, U.
    Asimakopoulos, D.N.
    Kambezidis, H.
    Helmis, C.G.
    Smedman, A.
    Atmospheric Environment - Part A General Topics, 1988, 22 (04): : 803 - 820
  • [50] A FIELD-STUDY OF THE WAKE BEHIND A 2 MW WIND TURBINE
    HOGSTROM, U
    ASIMAKOPOULOS, DN
    KAMBEZIDIS, H
    HELMIS, CG
    SMEDMAN, A
    ATMOSPHERIC ENVIRONMENT, 1988, 22 (04) : 803 - 820