Abstract
The spatial structure of turbulence in atmospheric boundary layer flows is highly relevant to wind energy. In particular, wind turbine control strategies based on inflow preview measurements require knowledge of the longitudinal evolution of turbulent flow as it approaches the rotor. These upstream measurements are usually obtained with nacelle-mounted wind lidars. In contrast to traditional in situ anemometry, lidars collect measurements within a probe volume which varies in size depending on the technology of the commercial system being used. Here, we address two issues related to the use of wind lidar to measure the incoming flow to a wind turbine: (i) whether existing longitudinal coherence models can be used to predict flow at the rotor, based on measurements performed at a distance away from the rotor; and (ii) what effect probe-volume averaging has on the inflow predictions. These two questions are critical to the design and implementation of robust wind turbine control strategies. To address these questions, we perform field measurements and large-eddy simulations to determine which incoming flow structures can be readily predicted with existing coherence models, and which require additional corrections to account for lidar volumetric averaging effects. Results reveal that the wind turbine induction zone has a negligible impact on the longitudinal coherence and first-order turbulence quantities, such as the standard deviation of velocity fluctuations. However, the phase of the signal, from which advection time periods of the turbulent structures are derived, is affected by the rotor blockage effect.
Highlights
Substantial gains in wind power plant performance and reliability can be achieved if wind turbines have preview information about the flow that is approaching to them and can predict its evolution in time to make flow-informed control decisions [1, 2]
We quantify the effect of the induction zone on the incoming flow and investigate whether existing longitudinal coherence models can accurately predict the evolution of turbulence structures along the mean wind direction
The results presented compare the performance of existing longitudinal coherence models, both in freestream and the induction zone, and discuss the limitations of lidar for measuring the coherence of atmospheric turbulence
Summary
Substantial gains in wind power plant performance and reliability can be achieved if wind turbines have preview information about the flow that is approaching to them and can predict its evolution in time to make flow-informed control decisions [1, 2]. The advection time of the measured flow is often estimated based on the frozen turbulence hypothesis [3], which is not valid for all turbulent eddy scales described by coherence models [4]. We quantify the effect of the induction zone on the incoming flow and investigate whether existing longitudinal coherence models can accurately predict the evolution of turbulence structures along the mean wind direction. The results presented compare the performance of existing longitudinal coherence models, both in freestream and the induction zone, and discuss the limitations of lidar for measuring the coherence of atmospheric turbulence These insights will be useful for future validation studies, coherence model improvements, and analysis of field measurements collected for wind turbine control based on inflow preview. The downstream signal is shifted in time based on the upstream wind speed and filtered based on the predicted wavenumber, providing a clear visualization of the advected structures
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