000197593 001__ 197593
000197593 005__ 20190812205742.0
000197593 037__ $$aCONF
000197593 245__ $$aA Large Eddy Simulation Study for upstream wind energy conditioning
000197593 269__ $$a2013
000197593 260__ $$c2013
000197593 336__ $$aConference Papers
000197593 520__ $$aThe wind energy industry is increasingly focusing on optimal power extraction strategies based on layout design of wind farms and yaw alignment algorithms. Recent field studies by Mikkelsen et al. (Wind Energy, 2013) have explored the possibility of using wind lidar technology installed at hub height to anticipate incoming wind direction and strength for optimizing yaw alignment. In this work we study the benefits of using remote sensing technology for predicting the incoming flow by using large eddy simulations of a wind farm. The wind turbines are modeled using the classic actuator disk concept with rotation, together with a new algorithm that permits the turbines to adapt to varying flow directions. This allows for simulations of a more realistic atmospheric boundary layer driven by a time-varying geostrophic wind. Various simulations are performed to investigate possible improvement in power generation by utilizing upstream data. Specifically, yaw-correction of the wind-turbine is based on spatio-temporally averaged wind values at selected upstream locations. Velocity and turbulence intensity are also considered at those locations. A base case scenario with the yaw alignment varying according to wind data measured at the wind turbine's hub is also used for comparison. This reproduces the present state of the art where wind vanes and cup anemometers installed behind the rotor blades are used for alignment control.
000197593 700__ $$0247477$$g206119$$aSharma, Varun
000197593 700__ $$0242907$$g165914$$aCalaf, Marc
000197593 700__ $$aParlange, Marc B.$$g155043$$0242902
000197593 7112_ $$dDecember 9-13, 2013$$cSan Francisco, USA$$aAGU Fall Meeting 2013
000197593 909C0 $$pEFLUM$$0252105$$xU11028
000197593 909CO $$pconf$$ooai:infoscience.tind.io:197593
000197593 917Z8 $$x219016
000197593 937__ $$aEPFL-CONF-197593
000197593 973__ $$rNON-REVIEWED$$sPUBLISHED$$aEPFL
000197593 980__ $$aCONF