It is well known that large amounts of wind energy are not effectively harvested in large wind farms because the turbines “shadow” each other and reduce the output of the turbines located in their wake. The wakes also produce increased turbulence and uneven loading on the shadowed turbines, increasing fatigue issues that eventually affect a wind farm’s longevity and reliability.
The Department of Energy’s Scaled Wind Farm Technology (SWiFT) facility was commissioned in 2013 in order to provide an experimental site with research-scale wind turbines for studying wind-turbine wakes and turbine–turbine interactions at a realistic scale. The SWiFT site is managed and operated by Sandia National Laboratories for the DOE Wind Program.
Wakes produced from upstream turbines in wind plants lead to lower power production and increased loads on downstream turbines. The resulting loss of energy capture and increase in maintenance costs represent one of the largest opportunities to reduce cost of energy (COE) at the plant level. Improvements in wind turbine design and plant layout to realize plant-scale COE reductions will require computational simulation and design tools with improved accuracy validated with experimental data.
This project seeks to demonstrate that the Sandia Wake Imaging System (SWIS) is capable of measuring the formation and development of flow structures near the turbine rotor at temporal and spatial scales not accessible by current measurement techniques such as scanning LIDAR or particle image velocimetry (PIV). The technique produces a velocity image of the measurement field by using specialized cameras with a filter and software to measure the Doppler shift of scattered laser light from aerosols tracking the flowfield.
In July of 2015, the SWIS was successfully deployed at the Scaled Wind Farm Technology (SWiFT) facility to demonstrate the tech¬nology in a field application (see image). When deployed as part of future test campaigns, this system will produce a novel experimental data for researchers to better understand fundamental wind-turbine wake phenomena and to validate computational codes and design tools that will be used to improve utility wind plant performance.
To establish a baseline with the Texas Tech University (TTU) [Ka-band (link1)] Doppler radar, unique and novel wind farm flow mapping has been performed in either full- or semi-precipitating environments. Preliminary results to date have opened insight to full utility-scale wind-farm performance that have never been seen in any other data set, measured or modeled.