{"title":"卷2紊流在风电场的结构","authors":"C. Meneveau","doi":"10.1615/tsfp10.630","DOIUrl":null,"url":null,"abstract":"In this presentation we provide an overview of our current understanding of the flow structure and turbulence in the wind turbine array boundary layer (WTABL). This particular type of shear flow develops when the atmospheric boundary layer interacts with an array of large wind turbines (Calaf et al. 2010, Cal et al. 2010, Stevens & Meneveau 2017). We distinguish between developing and fully developed WTABL and perform a series of Large Eddy Simulations that represent the turbines as actuator disks (see Figure 1 below). Salient LES results are synthesized in order to develop simplified analytical models needed for wind farm design and optimization. There one encounters the dichotomy of modeling individual turbine wakes or to model the wind farm flow as a boundary layer over a roughened surface whose properties depend upon the wind farm array. The coupled wake boundary layer model (Stevens et al. 2016a) attempts to match these two approaches iteratively. Ultimately, such models can lead to improved estimation of optimal wind turbine spacing including costs associated with covered surface, cabling and operation & maintenance (Stevens et al. 2016b). We also present new results on the temporal variability of wind power as measured in a wind tunnel experiment (Bossuyt et al. 2017) and its relationship to the spatio-temporal properties of turbulent boundary layers (Wilzcek et al. 2015). It turns out that as a first approximation, for situations without thermal stratification effects, one may consider the sum of turbine power to be a discrete sampling of the wavenumber-frequency spectrum of turbulent boundary layers. This model thus enables us to connect wind farm design parameters (turbine spacing, positioning, etc.) to fundamental properties of turbulent boundary layers.","PeriodicalId":266791,"journal":{"name":"Proceeding of Tenth International Symposium on Turbulence and Shear Flow Phenomena","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Volume 2The Structure Of Turbulent Flows In Wind Farms\",\"authors\":\"C. Meneveau\",\"doi\":\"10.1615/tsfp10.630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this presentation we provide an overview of our current understanding of the flow structure and turbulence in the wind turbine array boundary layer (WTABL). This particular type of shear flow develops when the atmospheric boundary layer interacts with an array of large wind turbines (Calaf et al. 2010, Cal et al. 2010, Stevens & Meneveau 2017). We distinguish between developing and fully developed WTABL and perform a series of Large Eddy Simulations that represent the turbines as actuator disks (see Figure 1 below). Salient LES results are synthesized in order to develop simplified analytical models needed for wind farm design and optimization. There one encounters the dichotomy of modeling individual turbine wakes or to model the wind farm flow as a boundary layer over a roughened surface whose properties depend upon the wind farm array. The coupled wake boundary layer model (Stevens et al. 2016a) attempts to match these two approaches iteratively. Ultimately, such models can lead to improved estimation of optimal wind turbine spacing including costs associated with covered surface, cabling and operation & maintenance (Stevens et al. 2016b). We also present new results on the temporal variability of wind power as measured in a wind tunnel experiment (Bossuyt et al. 2017) and its relationship to the spatio-temporal properties of turbulent boundary layers (Wilzcek et al. 2015). It turns out that as a first approximation, for situations without thermal stratification effects, one may consider the sum of turbine power to be a discrete sampling of the wavenumber-frequency spectrum of turbulent boundary layers. This model thus enables us to connect wind farm design parameters (turbine spacing, positioning, etc.) to fundamental properties of turbulent boundary layers.\",\"PeriodicalId\":266791,\"journal\":{\"name\":\"Proceeding of Tenth International Symposium on Turbulence and Shear Flow Phenomena\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceeding of Tenth International Symposium on Turbulence and Shear Flow Phenomena\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1615/tsfp10.630\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceeding of Tenth International Symposium on Turbulence and Shear Flow Phenomena","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1615/tsfp10.630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在本报告中,我们概述了我们目前对风力涡轮机阵列边界层(WTABL)中的流动结构和湍流的理解。当大气边界层与一系列大型风力涡轮机相互作用时,这种特殊类型的剪切流就会形成(Calaf et al. 2010, Cal et al. 2010, Stevens & Meneveau 2017)。我们区分了正在开发和完全开发的WTABL,并进行了一系列大涡模拟,将涡轮机表示为执行器盘(见下图1)。为了建立风电场设计和优化所需的简化分析模型,综合了显著的LES结果。在这里,人们遇到了对单个涡轮机尾迹进行建模或将风电场流动作为粗糙表面上的边界层进行建模的二分法,粗糙表面的特性取决于风电场阵列。耦合尾流边界层模型(Stevens et al. 2016a)试图迭代地匹配这两种方法。最终,这些模型可以改进对最佳风力涡轮机间距的估计,包括与覆盖面、布线和运行维护相关的成本(Stevens等人,2016b)。我们还提出了在风洞实验中测量的风电时间变异性的新结果(Bossuyt等人,2017)及其与湍流边界层时空特性的关系(Wilzcek等人,2015)。结果表明,作为第一近似,在没有热分层效应的情况下,可以认为涡轮功率的总和是湍流边界层波数-频谱的离散采样。因此,该模型使我们能够将风电场的设计参数(涡轮机间距、定位等)与湍流边界层的基本特性联系起来。
Volume 2The Structure Of Turbulent Flows In Wind Farms
In this presentation we provide an overview of our current understanding of the flow structure and turbulence in the wind turbine array boundary layer (WTABL). This particular type of shear flow develops when the atmospheric boundary layer interacts with an array of large wind turbines (Calaf et al. 2010, Cal et al. 2010, Stevens & Meneveau 2017). We distinguish between developing and fully developed WTABL and perform a series of Large Eddy Simulations that represent the turbines as actuator disks (see Figure 1 below). Salient LES results are synthesized in order to develop simplified analytical models needed for wind farm design and optimization. There one encounters the dichotomy of modeling individual turbine wakes or to model the wind farm flow as a boundary layer over a roughened surface whose properties depend upon the wind farm array. The coupled wake boundary layer model (Stevens et al. 2016a) attempts to match these two approaches iteratively. Ultimately, such models can lead to improved estimation of optimal wind turbine spacing including costs associated with covered surface, cabling and operation & maintenance (Stevens et al. 2016b). We also present new results on the temporal variability of wind power as measured in a wind tunnel experiment (Bossuyt et al. 2017) and its relationship to the spatio-temporal properties of turbulent boundary layers (Wilzcek et al. 2015). It turns out that as a first approximation, for situations without thermal stratification effects, one may consider the sum of turbine power to be a discrete sampling of the wavenumber-frequency spectrum of turbulent boundary layers. This model thus enables us to connect wind farm design parameters (turbine spacing, positioning, etc.) to fundamental properties of turbulent boundary layers.