University of Minnesota. Saint Anthony Falls LaboratorySandia National Laboratories. Wind Energy TechnologiesVirginia Tech. Aerospace and Ocean Engineering DepartmentYang, XiaoleiFoti, DanielKelley, Christopher L.Sotiropoulos, Fotis2015-07-282015-07-282015-06-11Zhang, D., & Paterson, E. (2015, June). System-level simulation of floating platform and wind turbine using high-fidelity and engineering models. Paper presented at the North American Wind Energy Academy 2015 Symposium, Blacksburg, VA.http://hdl.handle.net/10919/54658Turbine wake interaction is a key factor affecting wind farm performance and dynamic loadings on turbine structure. The Scaled Wind Farm Technology (SWiFT) facility (Barone and White., 2011, SANDIA REPORT, SAND2011-6522; Berg et al., AIAA 2014-1088), which is located at the Reese Technology Center near Lubbock, TX, USA, is specifically designed to enable investigating turbine wake effects at field scale. Three turbines (rotor diameter D = 27 m, hub height 31.5 m) forming a 3D-, 5D-, and 6D-length triangle have been installed. In this work, systematic study on wake interaction of the three SWiFT turbines, and how wake interaction affecting the power output and dynamic loadings under three different wind directions will be carried out. The VWiS (Virtual Wind Simulator) code (Yang et al. Wind Energy, 2014; Yang, Kang and Sotiropoulos, Physics of Fluids, 2012, vol 24, 115107; Kang, Yang and Sotiropoulos, Journal of Fluid Mechanics, 2014, vol 744, 376-403) developed at Saint Anthony Falls Laboratory, University of Minnesota is employed in the present simulations. In VWiS, the wind field is computed by solving the three-dimensional, unsteady, spatially-filtered continuity and Navier-Stokes equations. A dynamic Smagorinsky subgrid scale model is employed for the unresolved subgrid scales. The governing equations are discretized using second-order accurate, three-point central finite differencing for all spatial derivatives. The discrete equations are integrated in time using the second-order accurate fractional step method. The turbine blades are parameterized using a simplified actuator surface model, which accounts for the blades as separate rotating surfaces formed by the airfoil chords. The forces distributed on each blade are calculated based on a blade element approach. The forces from the actuator surfaces are distributed to the background grid nodes using the discrete delta function proposed in Yang et al. 2009 (Yang et al., Journal of Computational Physics, 2009, Vol. 228, pp. 7821-7836). The nacelle is represented by an improved nacelle model. Implementation of the employed actuator models for the blades and nacelle will be briefly presented. In this study, the cases considered are from the three most prevalent wind directions: South, West, and Southwest. For all the three turbines, the tip speed ratio, which is defined as the ratio of the tangential speed at the blade outer tip to the rotor disk-averaged wind speed at 1D upwind of the turbine, is 9. The turbulent flow at the inlet is calculated from separate large-eddy simulations. The roughness height of the ground is 0.01 m. The grid spacing near the turbine is D/100. Away from the turbine wake regions, the meshes are stretched in the crosswind and vertical directions. The meshes are uniformly distributed in the downwind direction based on the grid refinement study carried out in Yang et al. 2014 (Yang et al., Journal of Physics: Conference Series, 2014, Vol. 524, No. 1, p. 012139). For the instantaneous flowfields, wake meandering, which may significantly increase the dynamic loads on the downwind turbines, is observed for all the three turbines. In the conference, both instantaneous and time-averaged flowfields and the statistics of the power output and loads for the three cases will be presented.13 pagesapplication/pdfen-USIn CopyrightPresentationYang, XiaoleiFoti, DanielKelley, Christopher L.Sotiropoulos, Fotis