A longitudinal spatial coherence model for wind evolution based on large-eddy simulation

Standard feedback controllers on wind turbines can be augmented with feedforward control, relying on preview measurements of the wind provided by remote sensing instruments, to help regulate rotor speed and reduce structural loads. The effectiveness of feedforward control depends on how accurately the approaching wind can be measured. One significant cause of measurement error is the evolution of the wind as it travels toward the turbine from the measurement location. Wind evolution is commonly quantified using longitudinal spatial coherence to describe the decorrelation of turbulence as the wind advects downstream. In this paper, a collection of wind fields produced by large-eddy simulation is used to calculate longitudinal coherence for a variety of atmospheric conditions. Using the calculated coherence curves, we determine a simple longitudinal coherence formula for approximating wind evolution, which depends on mean wind speed, turbulent kinetic energy, and turbulence length scale. This formula is then used to find the optimal scan configurations that minimize measurement error for a preview-based control scenario employing Light Detection and Ranging. Results show how the optimal preview distance and achievable measurement error depend on the aforementioned wind parameters.