Wind Turbine Array Performance Based on Coupling CFD with Doppler Lidar Measurements

主要研究者：Peet，Yulia提案编号：1335868机构：亚利桑那州立大学题目：基于耦合CFD与多普勒激光雷达测量的风力涡轮机阵列性能随着现代风力涡轮机尺寸的增长，大气边界层（ABL）变化对其运行的影响变得更加重要。该项目将开发和验证一种新的方法，将多普勒激光雷达获得的现场风速测量结果整合到一个高保真的计算模型中，用于风力发电厂的流量和功率特性。多普勒激光雷达测量给出了最可靠的信息的微尺度气象结构调制的区域地形和当地的天气模式。基于大涡模拟（LES）的高保真风力发电厂流模型生成高分辨率的时空数据，包括用于评估结构响应和功率性能的不稳定涡轮机载荷。在真实大气测量的驱动下，LES模拟将为研究风力涡轮机阵列对随机大气环境的非定常响应提供宝贵的信息。 需要了解这些非定常响应，才能为风力涡轮机控制和风电场布局优化创建可靠的模型。将开发一种独特的多尺度方法，将实时观测捕获的亚中尺度大气运动的影响传播到风力发电厂和风力涡轮机。由粘性效应和叶片/尾流相互作用控制的风力涡轮机尺度。该方法将联合收割机结合多普勒激光雷达数据的最佳插值同化来检索矢量场信息，通过驱动辅助ABL LES模拟来重建较小的尺度以匹配激光雷达观测，并将同化的时空随机入流与基于LES和致动器线空气动力学的最先进的风力发电厂流动表征模型相结合。使用新的计算实验，PI将能够研究时空风变对不稳定涡轮机载荷和尾流物理特性的影响，并通过计算隔离不同的变率源，如风湍流、风速切变、风向切变，目的是表征这些效应的相对强度，并创建最可靠的简化流入模型，以捕获基本物理特性。简化模型的建立对于提高涡轮机行业的设计参数和标准至关重要。数值模拟基于阿贡国家实验室开发和支持的高阶谱元计算解算器Nek 5000，由于其高阶精度和极高的可扩展性，该解算器目前提供了最有效的高端计算资源利用率。了解风力发电厂对实际风况的时空响应将导致改进设计和减少不确定性，因此降低了均衡化能源成本（LCOE）。所吸取的经验教训和发现的专题将在科学界广泛传播。该项目将成为为当地高中学生提供实践研究和教育经验的中心主题。通过竞争性的多元化奖学金，PI将与四名高中学生，包括少数民族，女性和低收入学生，在该项目第二年的夏天。

PI: Peet, YuliaProposal Number: 1335868Institution: Arizona State UniversityTitle: Wind Turbine Array Performance Based on Coupling CFD with Doppler Lidar MeasurementsAs the size of the modern wind turbines grow, the effect of the atmospheric boundary layer (ABL) variability on their operation becomes significantly more important. This project will develop and validate a novel methodology to integrate field wind velocity measurements obtained by the Doppler lidar into a high-fidelity computational model for wind plant flow and power characterization. Doppler lidar measurements give the most reliable information of the microscale meteorological structures modulated by the regional terrain and local weather patterns. High-fidelity wind plant flow models based on Large Eddy Simulations (LES) generate highly-resolved spatio-temporal data including unsteady turbine loads for assessing the structural response and power performance. When driven by realistic atmospheric measurements, LES simulations will provide invaluable information to study the unsteady response of wind turbine arrays to the stochastic atmospheric environment. Knowledge of these unsteady responses is required to create reliable models for wind turbine control and wind farm layout optimization.A unique multiscale approach will be develop to propagate the effects of the sub-mesoscale atmospheric motion captured by the real-time observations down to the wind plant and wind turbine scales governed by the viscous effects and blade/wake interactions. This approach will combine the optimal interpolation assimilation of the Doppler lidar data to retrieve the vector field information, reconstructing the smaller scales by driving the auxiliary ABL LES simulations to match the lidar observations, and integrating the assimilated spatio-temporal stochastic inflow with the state-of-the-art wind plant flow characterization model based on LES and actuator line aerodynamics. Using a novel computational experiments the PIs will be able to study the effects of spatio-temporal wind variability on unsteady turbine loads and wake physics, and computationally isolate the different sources of variability such as wind turbulence, wind speed shear, wind directional shear, with the goal of characterizing the relative strengths of these effects and creating the most reliable simplified inflow models that capture the essential physics. The creation of simplified models is crucial for improving design parameters and standards for wind turbine industry. The numerical simulations are based on high-order spectral element computational solver Nek5000 developed and supported by Argonne National Laboratory that currently offers the most efficient utilization of high-end computing resources due to its high-order accuracy and extreme scalability.Understanding spatio-temporal responses of wind plants to realistic wind conditions will result in improved design and reduction of uncertainty, thus lowering Levelized Cost of Energy (LCOE). The lessons learned and the topics discovered will be broadly disseminated within the scientific community. This project will be a central theme for providing hands-on research and educational experience for the local high-school students. Through competitive diversity-oriented scholarships, PIs will work with four high-school students including minority, female and low-income students, over the summer following the second year of the project.