Turbulence upstream of wind turbines: A large-eddy simulation approach to investigate the use of wind lidars

Nacelle mounted wind lidars have been shown to be effective to detect turbulent events.

The upstream turbulence correlations have been shown to be ABL-stratification dependent.

Wind farm configuration modifies the background ABL flow and therefore the turbulent correlations.

The upstream distance can be determined as a function of the wind velocity and turbine readjustment time.

A truncated normal PDF model provides guidance on deciding the right upstream scanning distance.


Despite the evolution of wind turbines, the way in which in-situ meteorological information is obtained has not evolved much. Wind vane and cup anemometers, installed at the turbines nacelle, right behind the blades, are still used. This near-blade monitoring does not provide any time to readjust the profile of the wind turbine, and subjects the blades and structure to wind gusts and extreme incoming wind conditions. A solution is to install wind lidar devices on the turbine’s nacelle. This technique is currently under development as an alternative to traditional in-situ wind anemometry because it can measure the wind vector at substantial distances upwind. However, most used wind lidar systems are optimized for measuring within a fixed upwind range, but at what upwind distance should they interrogate the atmosphere? This work uses Large Eddy Simulations to create a realistic atmospheric flow to evaluate optimal scanning distances to learn about the incoming turbulence as a function of wind farm configuration and atmospheric stratification. A correlation model, based on a modified truncated normal distribution, has also been developed, which could be implemented within the feed-forward collective pitch control of the turbine, allowing for improved wind turbine readjustments.


  • Large eddy simulation;
  • Lidar;
  • Wind energy;
  • Wind farm;
  • Wind turbines;
  • Turbulent kinetic energy

Be the first to comment

Leave a Reply

Your email address will not be published.