Observations of the wake generated by a single utility-scale turbine and collected by the Texas Tech University Ka-band mobile research radars on 27 October 2011 are introduced. Remotely sensed turbine wake observations using lidar technology have proven effective; however, the presented radar capabilities provide a larger observational footprint and greater along-beam resolution than current scanning lidar systems. Plan-position indicator and range-height indicator scanning techniques are utilized to produce various wake analyses. Preliminary analyses confirm radial velocity and wind speed deficits immediately downwind of the turbine hub to be on the order of 50%. This introduction lays the groundwork for more in-depth analyses of wake structure and evolution using the Texas Tech University Ka-band radar systems, including wake meandering and wake-to-wake interaction in large wind park deployments.
The first known dual-Doppler (DD) measurements collected within a utility-scale wind farm are presented. Various complex flow features are discussed, including detailed analyses of turbine wakes, turbine-to-turbine interaction, high wind speed channels that exist between individual wakes and intermittent gust propagation. The data have been collected using innovative mobile Doppler radar technologies, which allows for a large observational footprint of~17 km 2 in the presented analyses while maintaining spatial resolution of 0.49°in the azimuthal dimension by 15 m in the along-beam range dimension. The presented DD syntheses provide three-dimensional fields of the horizontal wind speed and direction with a revisit time of approximately 1 min. DD wind fields are validated with operational turbine data and are successfully used to accurately project composite power output for several turbines. The employed radar technologies, deployment schemes, scanning strategies and subsequent analysis methodologies offer the potential to contribute to the validation and improvement of current wake modeling efforts that influence wind farm design and layout practices, enhanced resource assessment campaigns, and provide real-time wind maps to drive 'smart' wind farm operation.
Typical methods used to acquire wind profiles from Doppler radar measurements rely on plan position indicator (PPI) scans being performed at multiple elevation angles to utilize the velocity-azimuth display technique or to construct dual-Doppler synthesis. These techniques, as well as those employed by wind profilers, often produce wind profiles that lack the spatial or temporal resolution to resolve finescale features. If two radars perform range-height indicator (RHI) scans (constant azimuth, multiple elevations) along azimuths separated by approximately 908, then the intersection of the coordinated RHI planes represents a vertical set of points where dual-Doppler wind syntheses are possible and wind speed and direction profiles can be retrieved. This method also allows for the generation of high-resolution wind time histories that can be compared to anemometer time histories. This study focuses on the use of the coordinated RHI scanning strategy by two high-resolution mobile Doppler radars in close proximity to a 200-m instrumented tower. In one of the first high-resolution, long-duration comparisons of dual-Doppler wind synthesis with in situ anemometry, the mean and turbulence states of the wind measured by each platform were compared in varying atmospheric conditions. Examination of mean wind speed and direction profiles in both clear-air (nonprecipitating) and precipitating environments revealed excellent agreement above approximately 50 m. Below this level, dual-Doppler wind speeds were still good but slightly overestimated as compared to the anemometer-measured wind speeds in heavy precipitation. Bulk turbulence parameters were also slightly underestimated by the dual-Doppler syntheses.
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