An Integrated Approach To Offshore Wind Energy Assessment: Great Lakes 3D Wind Experiment

This grant supported fundamental research into the characterization of flow parameters of relevance to the wind energy industry focused on offshore and the coastal zone. A major focus of the project was application of the latest generation of remote sensing instrumentation and also integration of measurements and numerical modeling to optimize characterization of time-evolving atmospheric flow parameters in 3-D. Our research developed a new data-constrained Wind Atlas for the Great Lakes, and developed new insights into flow parameters in heterogeneous environments. Four experiments were conducted during the project: At a large operating onshore wind farm in May 2012; At the National Renewable Energy Laboratory National Wind Technology Center (NREL NWTC) during February 2013; At the shoreline of Lake Erie in May 2013; and At the Wind Energy Institute of Canada on Prince Edward Island in May 2015. The experiment we conducted in the coastal zone of Lake Erie indicated very complex flow fields and the frequent presence of upward momentum fluxes and resulting distortion of the wind speed profile at turbine relevant heights due to swells in the Great Lakes. Additionally, our data (and modeling) indicate the frequent presence of low level jets at 600 m height over the Lake and occasions when the wind speed profile across the rotor plane may be impacted by this phenomenon. Experimental data and modeling of the fourth experiment on Prince Edward Island showed that at 10-14 m escarpment adjacent to long-overseas fetch the zone of wind speed decrease before the terrain feature and the increase at (and slightly downwind of) the escarpment is ~3–5% at turbine hub-heights. Additionally, our measurements were used to improve methods to compute the uncertainty in lidar-derived flow properties and to optimize lidar-scanning strategies. For example, on the basis of the experimental data we collected plus those from one of our research partners we advanced a new methodology to estimate a priori the uncertainty in wind speed retrievals from arc scans based on site characteristics such as wind velocity, turbulence intensity and proposed scan geometry. Insights regarding use of remote sensing technologies deriving from project experiments were used to compile a best practice document http://doi.org/10.7298/X4QV3JGF for measuring wind speeds and turbulence offshore through in-situ and remote sensing technologies. A project-specific web-site was developed and is available at: http://www.geo.cornell.edu/eas/PeoplePlaces/Faculty/spryor/DoE_AIATOWEA/index.html

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