为综合研究风力机尾流特性,将尾流区域分为近尾流区域和远尾流区域,并考虑风切变效应引起的风速差对尾流速度的影响,提出一种基于动量理论的三维工程全尾流模型（3DFM）。与风场实测数据对比,3DFM模型的近尾流区预测精度高达95.82%,远尾流区预测精度高达95.00%,验证了模型的有效性和准确性。根据来流风不同大气稳定状态修正尾流膨胀系数和风切变系数,详细研究大气稳定状态对尾流速度分布和恢复的影响。研究结果表明大气层越稳定,风切变系数越高,下游相同位置处的尾流区域面积越大,尾流速度恢复得越慢。
Abstract
In this article, a three-dimensional engineering full wake model （3DFM model） based on the momentum theory is proposed to study the wake characteristics of wind turbines. The 3DFM model not only divides the wake region into the near-wake region and the far-wake region; but also considering the influence of wind shear effect on wake velocity. The validity and accuracy of 3DFM model are verified by the measured data of wind farm. The prediction accuracy of 3DFM model is as high as 95.82% in the near-wake region and 95.00% in the far-wake region, which verifies the validity and accuracy of the model. The wake expansion coefficient and wind shear coefficient are modified according to the different atmospheric stable states of the inflow wind, and the influence of the atmospheric stable state on the wake velocity distribution and recovery is studied in detail. The results show that the more stable the atmosphere, the higher the wind shear coefficient, the larger the wake area at the same position downstream, and the slower the wake speed recovery.
关键词
尾流效应 /
风电场 /
风力机 /
全尾流 /
风切变效应 /
大气稳定性
Key words
wake effects /
wind farm /
wind turbines /
full wake /
wind share /
atmospheric stability
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参考文献
[1] SHAKOOR R, HASSAN M Y, RAHEEM A, et al.Wake effect modeling: a review of wind farm layout optimization using Jensen's model[J]. Renewable and sustainable energy reviews, 2016, 58: 1048-1059.
[2] JENSEN N O.A note on wind generator interaction[R]. Risø National Laboratory (Risø-M-2411), 1983.
[3] TIAN L L, ZHU W J, SHEN W Z, et al.Development and validation of a new two-dimensional wake model for wind turbine wakes[J]. Journal of wind engineering and industrial aerodynamics, 2015, 137: 90-99.
[4] GE M W, WU Y, LIU Y Q, et al.A two-dimensional Jensen model with a Gaussian-shaped velocity deficit[J]. Renewable energy, 2019, 141: 46-56.
[5] KEANE A.Advancement of an analytical double-Gaussian full wind turbine wake model[J]. Renewable energy, 2021, 171: 687-708.
[6] GAO X X, YANG H X, LU L.Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model[J]. Applied energy, 2016, 174: 192-200.
[7] JEON S, KIM B, HUH J.Study on methods to determine rotor equivalent wind speed to increase prediction accuracy of wind turbine performance under wake condition[J]. Energy for sustainable development, 2017, 40: 41-49.
[8] 宋翌蕾, 田琳琳, 赵宁. 风力机三维尾流模型的提出与校核[J]. 太阳能学报, 2021, 42(2): 129-135.
SONG Y L, TIAN L L, ZHAO N.Proposal and validation of a new 3D wake model for wind turbine[J]. Acta energiae solaris sinica, 2021, 42(2): 129-135.
[9] HE R Y, YANG H X, SUN H Y, et al.A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes[J]. Applied energy, 2021, 296: 117059.
[10] GAO X X, ZHANG S H, LI L Q, et al.Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test[J]. Energy, 2022, 254: 124277.
[11] ISMAIEL A.Wind turbine blade dynamics simulation under the effect of atmospheric turbulence[J]. Emerging science journal, 2022, 7(1): 162-176.
[12] DU B W, GE M W, ZENG C J, et al.Influence of atmospheric stability on wind-turbine wakes with a certain hub-height turbulence intensity[J]. Physics of fluids, 2021, 33(5): 055111.
[13] 彭秀芳, 王磊, 项雯, 等. 热稳定性对近海风电场影响研究[J]. 太阳能学报, 2019, 40(1): 242-248.
PENG X F, WANG L, XIANG W, et al.Study on influence of atmospheric stability on offshore windfarm[J]. Acta energiae solaris sinica, 2019, 40(1): 242-248.
[14] PACHECO DE SÁSARMIENTO F I, GOES OLIVEIRA J L, PASSOS J C. Impact of atmospheric stability, wake effect and topography on power production at complex-terrain wind farm[J]. Energy, 2022, 239: 122211.
[15] VERMEER L J, SØRENSEN J N, CRESPO A. Wind turbine wake aerodynamics[J]. Progress in aerospace sciences, 2003, 39(6): 467-510.
[16] AITKEN M L, BANTA R M, PICHUGINA Y L, et al.Quantifying wind turbine wake characteristics from scanning remote sensor data[J]. Journal of atmospheric and oceanic technology, 2014, 31(4): 765-787.
[17] BASTANKHAH M, PORTÉ-AGEL F.Experimental and theoretical study of wind turbine wakes in yawed conditions[J]. Journal of fluid mechanics, 2016, 806: 506-541.
[18] 邱颖宁, 刘毅, 冯延晖. 基于空间变化的风力机三维尾流风速计算方法: CN115062563A[P].2022-09-16.
[19] MCKENNA R, LEYE P O V D, FICHTNER W. Key challenges and prospects for large wind turbines[J]. Renewable and sustainable energy reviews, 2016, 53: 1212-1221.
[20] GAO X X, LI B B, WANG T Y, et al.Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements[J]. Applied energy, 2020, 260: 114272.
[21] BARTHELMIE R J, FOLKERTS L, LARSEN G C, et al.Comparison of wake model simulations with offshore wind turbine wake profiles measured by sodar[J]. Journal of atmospheric and oceanic technology, 2006, 23(7): 888.
[22] KIM D Y, KIM Y H, KIM B S.Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear[J]. Energy, 2021, 214: 119051.
[23] KIM H, MOON C J, KIM Y G, et al.Analysis of atmospheric stability for the prevention of coastal disasters and the development of efficient coastal renewable energy[J]. Journal of coastal research, 2021, 114: 241-245.
[24] VENAYAGAMOORTHY S K, KOSEFF J R.On the flux Richardson number in stably stratified turbulence[J]. Journal of fluid mechanics, 2016, 798: R1.
[25] PEÑA A, RÉTHORÉ P E, RATHMANN O. Modeling large offshore wind farms under different atmospheric stability regimes with the Park wake model[J]. Renewable energy, 2014, 70: 164-171.
[26] GRACHEV A A, FAIRALL C W.Dependence of the monin-obukhov stability parameter on the bulk Richardson number over the ocean[J]. Journal of applied meteorology, 1997, 36(4): 406-415.
基金
河北省省级科技计划（21567605H）;基于无线网络全覆盖的海上风电安全生产管理平台建设研究与应用（XT-KJ-2021012）
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