Lidar Wind Preview Quality Estimation for Wind Turbine Control

Abstract

Lidar-assisted wind turbine control has been proven to be beneficial for wind turbines. This technology uses the preview of rotor-effective wind speed obtained from lidar measurements in front of the wind turbine. The wind preview allows the controller to react to the disturbance prior to the impact on the turbine. However, the quality of the wind preview provided by a lidar is constantly changing mainly with atmospheric conditions and usually only the lower frequency components of the signal can be used for control. Thus, it is necessary to estimate the wind preview quality online and accordingly adjust the filter parameters to remove the uncorrelated information and to schedule controller parameters. Previously, the wind preview quality during short field testing campaigns has been identified offline prior to using the lidar signal for control. This was done with a frequency-based correlation study by comparing the rotor-effective wind speed estimated from turbine data to the one provided by the lidar. An online application of the frequency-based correlation study however is hard to implement due to the limitation of the estimation from turbine data, the amount of data necessary, and the sensitivity of the frequency-based method itself. In this paper, we develop a new statistic-based method to estimate the wind preview quality by only using the data from a pulsed lidar system without the need of wind turbine data. The method is assessed using simulated lidar measurement scanning an unfrozen wind field. The results show that the method is able to distinguish the preview quality under different wind evolution conditions.

Updates on the OpenFAST Lidar Simulator

“…We use the typical definition of rotor effective wind speed (REWS) for control purposes, which is the mean longitudinal wind component over the rotor swept area [18,11,21,9] at rotor position u R and the one estimated by lidar u L can be calculated by [9]:…”

Four-dimensional wind field generation for the aeroelastic simulation of wind turbines with lidars

“…The reason for that is that the LAC system uses turbulence signals taken at some distance upwind as input, but the turbulence will evolve before it reaches the turbine -this physical phenomenon is called wind evolution . Thus, the turbine will not be exposed to exactly the same disturbances as that measured by the lidar (Guo and Schlipf, 2021). To make it possible to simulate this effect in stochastic wind field simulations and to assess the benefits of LAC more reasonably, Taylor's hypothesis should no longer be applied, and wind evolution must be taken into account.…”