US: Scientists at Pacific Northwest National Laboratory will map the wind patterns off the Oregon coast in a new demonstration project announced by the US Department of Energy (DOE). As part of the US government”s “all of the above” strategy to develop more secure, domestic energy sources, the DOE announced seven offshore wind demonstration projects with an initial phase investment of USD 4 million each over 2 years.
One project, led by Principle Power, based in Seattle, will support the WindFloat Pacific Demonstration Project, sited in Coos Bay, Oregon. PNNL is leading the resource assessment team, first to identify the amount of wind available at the site, then to optimise the site location based on wind resources. Using mesoscale meteorological models and dual-Doppler LiDAR measurements, they will map the wind field and project the estimated wind at potential sites from onshore and offshore locations.
“Using coordinated LiDAR with meteorological models is a new method of assessment of wind energy in the boundary layer of the atmosphere, just above Earth,” said Dr. Will Shaw, team lead and meteorologist at PNNL. “Weather buoys just don”t provide the kind of measurements needed to accurately describe wind resources that would drive these 6-megawatt turbines.”
In the first phase of the assessment, the team, including PNNL scientists Drs. Larry K. Berg and Rob K. Newsom, will deploy dual Doppler scanning LiDAR on the Oregon coastline aimed out to sea. LiDAR is a remote-sensing laser instrument acquiring detailed wind measurements used in atmospheric research. Two LiDARs working together can provide a map of the wind speed and direction over large areas. These measurements will provide information that will validate the models used to help optimally locate the offshore turbine field. In the next phase, they will deploy LiDARs off shore, on the turbine platforms. Data gathered during this phase will provide detailed measurements of the wind coming into the turbine array and the wakes induced by the turbines. The measurements will be used to validate and optimise the meteorological models, providing ongoing information for project operation.