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风能利用中的空气动力学研究进展Ⅱ:入流和尾流特性

王同光 田琳琳 钟伟 王珑 朱呈勇

王同光, 田琳琳, 钟伟, 等. 风能利用中的空气动力学研究进展Ⅱ:入流和尾流特性[J]. 空气动力学学报, 2022, 40(4): 22−50 doi: 10.7638/kqdlxxb-2021.0390
引用本文: 王同光, 田琳琳, 钟伟, 等. 风能利用中的空气动力学研究进展Ⅱ:入流和尾流特性[J]. 空气动力学学报, 2022, 40(4): 22−50 doi: 10.7638/kqdlxxb-2021.0390
WANG T G, TIAN L L, ZHONG W, et al. Aerodynamic research progress in wind energy Ⅱ: Inflow and wake characteristics[J]. Acta Aerodynamica Sinica, 2022, 40(4): 22−50 doi: 10.7638/kqdlxxb-2021.0390
Citation: WANG T G, TIAN L L, ZHONG W, et al. Aerodynamic research progress in wind energy Ⅱ: Inflow and wake characteristics[J]. Acta Aerodynamica Sinica, 2022, 40(4): 22−50 doi: 10.7638/kqdlxxb-2021.0390

风能利用中的空气动力学研究进展Ⅱ:入流和尾流特性

doi: 10.7638/kqdlxxb-2021.0390
基金项目: 国家重点研发计划(2019YFE0192600,2019YFB1503700);国家自然科学基金青年科学基金(11802122)
详细信息
    作者简介:

    王同光*(1962-),男,山东蓬莱人,教授,研究方向:风力机空气动力学. E-mail: tgwang@nuaa.edu.cn

  • 中图分类号: TM315

Aerodynamic research progress in wind energy Ⅱ: Inflow and wake characteristics

  • 摘要: 空气动力学是风能工程面临的首要和关键问题之一,决定着风工程的经济性、稳定性和安全性。针对风能技术发展的迫切需求,结合近年来风能设备大型化、规模化、海洋化、智能化和数字化的发展趋势,对风能利用中的空气动力学问题进行了探讨,本篇为其中第二部分:入流和尾流特性。一方面,选取大气边界层、风力机尾流、陆上/海上/复杂地形风电场混合尾流及其之间的相关干扰等典型气动问题为论述对象。另一方面,从外场测量、风洞实验、理论分析、数值模拟、工程建模和人工智能等多种研究途径着手,梳理其中涉及的关键空气动力学问题、特殊物理现象及取得的重要研究进展,分析所涉及的流动分布特性、演变规律与关键流动机理。此外,结合我国气候、地理条件、国情探讨风电发展面临的空气动力学难题并尝试给出解决策略。最后,对未来的研究方向进行展望。以期为风电的行业规划、技术发展和工程实施提供重要参考。
  • 图  1  陆上大气边界层(白天和晚上两个不同时段)的结构及与风电场相互作用示意图

    Figure  1.  Schematic of the onshore atmospheric boundary layer (ABL) structures during the day and night as well as the interaction with the wind farm

    图  2  风力机尾涡结构示意图(尖速比λ = 7.07工况条件下Tjaereborg风力机尾涡模拟,根据文献[7]重绘)

    Figure  2.  Schematic diagram of vortex structure in the wake of a wind turbine (Tjaereborg wind turbine at a tip speed ratio λ = 7.07, adapted from reference [7])

    图  3  盐雾天气下航拍到的Horns Rev海上风电场尾流图[10]

    Figure  3.  Aerial image of the wind turbine wakes of the Horns Rev wind farm under a low hanging fog condition[10]

    图  4  风力机空气动力学研究中所涉及的多尺度问题(从翼型尺度到气象中尺度)

    Figure  4.  Schematic diagram of the multi-scale problem in the wind turbine aerodynamic research(from the airfoil scale to the meteorological mesoscale)

    图  5  陆上典型大气边界层分层结构示意图

    Figure  5.  Schematic of the onshore ABL structure

    图  6  典型大气条件下的风速廓线及速度脉动功率谱分布(根据文献[14]的结果重绘)

    Figure  6.  Wind speed profiles and vertical velocity fluctuation power spectra under typical atmospheric conditions (adapted from references [14])

    图  7  陆上高压区大气稳定度及边界层结构的日变化示意图

    Figure  7.  Diurnal variation of the atmospheric stability and the ABL structure for overland regions

    图  8  日周期内不同高度位置的风资源信息演变(LES仿真)[31]

    Figure  8.  Diurnal evolution of the wind resource at various altitudes (simulated by LES)[31]

    图  9  风力机周围流场区及各区域典型特性示意图

    Figure  9.  Schematic of flow regions around a wind turbine and their characteristics

    图  10  风力机下游叶尖和叶根涡发展演变示意图[34]

    Figure  10.  Schematic of the tip and root vortices evolution downstream the wind turbine[34]

    图  11  两种湍流模拟方法(PANS和LES)计算到的风力机轮毂高度平面涡量图[62]

    Figure  11.  Vorticity contours at the hub-height horizontal section obtained from PANS and LES [62]

    图  12  风力机尾流蜿蜒示意图[18]

    Figure  12.  Schematic of the meandering motion of a wind turbine wake[18]

    图  13  SOWFA和深度学习模型POD-LSTM计算到的两台风力机尾流相互干扰[97]

    Figure  13.  SOWFA and POD-LSTM model prediction for the wake interaction between two wind turbines[97]

    图  14  考虑大气稳定度因素的风电场尾流场发展演变过程及其与大气边界层的相互作用示意图(根据文献[8]重绘)

    Figure  14.  Schematic of the wind farm wake region evolution and its interaction with a stratified ABL (adapted from reference [8])

    图  15  基于风场测量数据的数值计算方法验证:Horns Rev海上风电场总发电功率与风向之间的关系[59]

    Figure  15.  Validation of numerical methods based on wind farm measured data: total power outputas a function of the incoming wind direction for the Horns Rev wind farm[59]

    图  16  AD/LES计算得到的大型风场垂直动量输运效应(小圆盘代表风力机)[113]

    Figure  16.  AD/LES computed vertical momentum transport effect for a large wind farm (wind turbines are represented by small white disks)[113]

    图  17  基于中尺度WRF模式计算得到的风电场尾流场速度分布云图[115]

    Figure  17.  Velocity contours of the wind farm wake flow field computed by the WRF model[115]

    图  18  经典“自上而下”模型的原理示意图[8]

    Figure  18.  Principle diagram of classical top-down models[8]

    图  19  优化后的风电场机组布局分布图[141]

    Figure  19.  Wind farm layout after optimization[141]

    图  20  考虑地形效应计算得到的风电场速度云图 [164]

    Figure  20.  Velocity contour of the wind farm simulation with the terrain effect[164]

    图  21  基于WRF模式结合风电场参数化建模方法预测到的风电场某一高度平面Hhub = 80 m速度分布云图[177]

    Figure  21.  Velocity contours at Hhub = 80 m of a wind farm prediced by the WRF model coupled with the wind farmparametric modelling[177]

    表  1  风力机周围流场的特点

    Table  1.   Flow characteristics around a wind turbine

    类型位置特点
    诱导区 上游1D 由于风力机实体的阻塞作用,造成风速下降
    近尾流区 下游2D~4D 流场分布取决于叶片的几何外形和数目、塔架、机舱以及来流大气属性。表现为高度复杂的三维各向异性流动
    远尾流区 下游≥4D 主要受风力机气动特性(如功率、推力特性)、大气湍流(地表粗糙度和大气稳定度)和尾流等影响。表现为具有自相似特点的各向同性流动
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  • 收稿日期:  2021-06-29
  • 修回日期:  2021-10-12
  • 录用日期:  2021-11-17
  • 网络出版日期:  2021-12-21
  • 刊出日期:  2022-08-10

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