3.1
Spatial Characteristics of Power Variability from a Large Wind Farm in Iowa during the 2013 Crop/ Wind Energy Experiment (CWEX-13)

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Monday, 5 January 2015: 4:00 PM
224B (Phoenix Convention Center - West and North Buildings)
Daniel A. Rajewski, Iowa State Univ., Ames, IA; and E. S. Takle, J. K. Lundquist, S. L. Irvin, and R. K. Doorenbos
Manuscript (734.3 kB)

Large wind farms constructed over the U.S. Midwest operate under a variety of meteorological conditions determined by synoptic systems and boundary layer processes with the diurnal cycle. Nighttime thermal stratification, shears in wind speed and in wind direction, and turbulence between the top and bottom of the turbine rotor induce loading on turbine components and contribute to frequent periods of turbine under-performance. Turbine wakes reduce total farm power according to inflow conditions (hub speed, turbulence intensity, thermal stratification) and the orientation of the turbines within the wind farm. Numerical simulations and wind tunnel experiments propose optimal number, orientation, and spacing of turbines within wind farms but very few measurements from onshore wind farms are available for validation of these modeling approaches. The 2013 Crop Wind Energy Experiment (CWEX-13) expands on measurements that were taken earlier between the leading two lines of turbines within a 300 MW wind farm in Iowa (CWEX-10/11). CWEX-13 provides a better understanding of turbine wakes within several lines of turbines of a wind farm from a combination of in situ measurements from surface flux towers and profiling and scanning LiDARs.

In this study we apply surface flux measurements from seven locations to classify power differences between turbines according to thermal stability and wind direction. SCADA measurements of nacelle wind speed, yaw angle and produced power from the northwest third of turbines in the wind farm determine when the turbines were operational or offline. LiDAR profiles of wind speed and wind direction upwind and downwind of the leading two turbine lines facilitate detection of turbine wakes between the 40-120 m rotor-layer. Surface stability and wind direction categories are combined with SCADA to depict multiple spatial composites of the power ratios between turbines. Nighttime composites of the surface station differences in turbulence kinetic energy and coherent turbulence kinetic energy demonstrate the applicability of using surface measurements to detect power losses from turbine wakes.

A case study between 0 UTC July 22 to 12 UTC July 23 illustrates a temporal-spatial example of wake interactions and power variability for ramping events before, during, and after the passage of a leading stratiform MCS. In the first overnight period (02-10 UTC July 22), with wind directions from 160-190, power is reduced by 50-75% at the northern portion of the wind farm for hub-height winds of 4-6 ms-1. Before the arrival of the convective activity (18-22 UTC July 23), hub height wind speeds are between 5-10 ms-1 out of 200-240 and 20-40% increases in power are observed in scattered regions of the wind farm.