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