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

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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.