Measurement-Driven Large-Eddy Simulations of a Diurnal Cycle during a Wake Steering Field Campaign

Abstract

Abstract. High-fidelity flow modeling with data assimilation enables accurate representation of the wind-farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and controls inputs. This paper covers the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that captured local flow conditions within a large-eddy simulation (LES), given observations that do not completely describe the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 hours after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0° to 17°. To resolve these nonstationary nighttime conditions, the turbulence field was evolved starting from the diurnal cycle of the previous day. Given these simulated background conditions, an LES with actuator-disk turbines was compared to a steady-state engineering wake model, demonstrating agreement with measurements under partially and nearly waked conditions. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by 10 %.

Wind Farm Structural Response and Wake Dynamics for an Evolving Stable Boundary Layer: Computational and Experimental Comparisons

“…An ultrasonic anemometer on the meteorological mast provides 20-Hz u-, v-, and w-velocity components; additional sensors provide virtual temperature, pressure, and humidity. The profiling Doppler lidar provides 1-Hz wind speed and wind direction data from 40to 260-m heights with an interval of 20 m. A detailed list of all inflow measurements used to construct the high-fidelity inflow is provided in Quon (2023), which also provides more information on the inflow wind properties, measurements, wake steering campaign details, and why this time period was selected.…”

“…The loads measurement campaign took place from December 10, 2019 through February 16, 2020. However, this work focuses on the 3.5-hour period between 7 : 30-11 : 00 UTC on December 26, 2019, as detailed in Quon (2023).…”

“…This is due to the the induction zone upstream of the turbines captured by SOWFA, which reduces the inflow velocity experienced by the wind turbines. The time-varying shear exponent was computed using profiling lidar data and based on changes to the wind speed between heights of 40 and 120 m. These measurements show a wide range of shear exponents during this time period, and at times large gradients, indicating that the background conditions are not stationary as discussed in Quon (2023). This is important when comparing simulated results and measured data, and this nonstationarity can have a significant impact on the ability of a code to accurately capture rotor response.…”