Dependence of wind turbine wake behavior on atmospheric stability, as measured by long-range Doppler lidar

To support substantial deployment of renewably-generated electricity from the wind, critical information about the variability of wind turbine wakes in the real atmosphere from multi-MW turbines is required. The assessment of the velocity deficit and turbulence associated with industrial-scale turbines is a major issue for wind farm design, particularly with respect to the optimization of the spacing between turbines. The significant velocity deficit and turbulence generated by upstream turbines can reduce the power production and produce harmful vibrations in downstream turbines, which can lead to excess maintenance costs. The complexity of wake effects depends on many factors arising from both hardware (turbine size, rotor speed, and blade geometry, etc.) and from meteorological considerations such as wind velocity, gradients of wind across the turbine rotor disk, atmospheric stability, and atmospheric turbulence.

To characterize the relationships between the meteorological inflow and turbine wakes, a collaborative field campaign was designed and carried out at the Department of Energy's National Wind Technology Center (NREL/NWTC) in south Boulder, Colorado, in spring 2011. This site often experiences channeled flow with a consistent wind direction, enabling robust statistics of wake velocity deficits and turbulence enhancements. Using both in situ and remote sensing instrumentation, measurements upwind and downwind of multi-megawatt wind turbine in complex terrain quantified the variability of wind turbine inflow and wakes from an industrial-scale turbine. The turbine of interest has a rated power of 2.3 MW, a rotor diameter of 100m, and a hub height of 80m. In addition to several meteorological towers, one extending to hub height (80m) and another extending above the top of the rotor disk (135m), a Triton mini-sodar and a Windcube lidar characterized the inflow to the turbine and the variability across the site. The centerpiece instrument of the TWICS campaign was the NOAA High Resolution Doppler lidar (HRDL), a scanning lidar which captured three-dimensional images of the turbine inflow and wake. Over several weeks, 48+ hours of HRDL observations during a variety of wind speed and atmospheric stability conditions were collected using three scanning strategies.

In this presentation, we present analytical techniques to distinguish wakes from the background variability. Wakes are then classified by width, height, velocity deficit, and turbulence levels based on atmospheric stability and inflow conditions. The wake structure is observed to depend on atmospheric stability, with higher velocity deficits and wider wakes in stable conditions than in unstable periods. By integrating these advanced observational capabilities with innovative approaches to atmospheric modeling, this work will help to improve simulation tools used to quantify power loss and fatigue loading due to wake effects, thereby aiding the optimization of wind farm layouts.