Wave driven wind simulations with CFD

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1 Wave driven wind simulations with CFD DeepWind'2013, January, Trondheim, Norway Siri Kalvig 1, Richard Kverneland 2 and Eirik Manger 3 1 StormGeo, Norway 2 University of Stavanger, Norway 3 Acona Flow technology, Norway

2 Introduction Motivation Wave-wind interactions Method Results Conclusions & comments Industrial PhD of Stormgeo and UiS and PhD is part of NORCOWE.

3 Motivation Statoil s Hywind Norway, Photo; Lene Eliassen A typical offshore wind picture. How does a non-flat sea affect the wind fields?

4 Motivation Will wave induced wind at an offshore wind site result in different wind shear and more turbulence than expected? And if so, how will this affect the turbines?

5 Wind wave interaction Wind sea and swell influences the atmosphere different! Wind sea Swell - generated by local wind - long period generated by distant storms Most common is a mixture of wind sea and swell, and this makes the picture even more complicated.

6 Wind wave interaction Field experiments and numerical simulations show that during swell conditions the wind profile will no longer exhibit a logarithmic shape and the surface drag relies on the sea state (i.e. Smedman et al & 2009, Semedo et al. 2009). There is a gap between best knowledge (science) and best practice (codes, standards) and there is a need for improved guidance on the impact atmospheric stability and wave-wind interaction in the MABL can have on the offshore wind industry (Kalvig et al 2013, Wiley Wind Energy, in press) Swell can result in both higher and smaller effective surface drag and it is likely that swell can create different wind shear and turbulence characteristics so that a wind turbine site will be exposed to other external environmental condition than it was designed for.

7 Wind wave interaction Sullivan et al. (2008) developed a large-eddy simulation (LES) with a two-dimensional sinusoidal wave and identified flow responses for three cases; wind opposing swell, wind following swell and wind over a swell surface with no movement. The flow responses in the different cases where very different and fingerprints of the surface wave extended high up in the MBL. Aim at develop a wave-wind simulation set up with open source CFD and with more computational effective methods.

8 Method Need to simulate wave movements! From: Grand Valley State University, Need a new boundary condition that take into account the sinusoidal movement of the ground. Solution: Transient OpenFOAM simulation with pimpledymfoam. New boundary condition implemented with mesh transformations.

9 Method Need to simulate wave movements! From: Grand Valley State University, Need a new boundary condition that take into account the sinusoidal movement of the ground. Solution: Transient OpenFOAM simulation with pimpledymfoam. New boundary condition implemented with mesh transformations.

10 Method The open source CFD toolbox OpenFOAM is used for both mesh generation and CFD computations. Wave speeds (c), wave amplitude (a), wave length (L) are input parameters to the model. To start with a relatively small domain with length of 250 m and a height of 50 m was established. Various sensitivity analyses were performed where different wind velocities and sea states where studied in detail (Kverneland, master theses UiS 2012). Temperature and the Coriolis effect are not taking into account and only uniform wind is studied. The calculations use a Reynolds averaging Navier-Stokes (RANS) approachs and since the wave moves it is necessary with a transient (time varying) simulation. The turbulence closure model used is the standard k-epsilon model.

11 Method NORCOWE & NOWITECH organized a wind turbine blind test in , BT1 & BT2. BT1: Eight independent modelling groups submitted 11 sets of simulations. No obvious winner and large spread of results (Krogstad et.al. 2011). Currently working with the Actuator disk and actuator line method. Aiming at coupling the wave set up with a turbine wake model.

12 Results wind wind following wind wind opposing In general: The wind speed profile and the turbulent kinetic energy pattern far above the will be different depending on the wave state and wave direction.

13 Results Wind aligned with : Vertical profile (at x=210 m) of mean values of the horizontal and vertical component of the wind flow for six cases with different inlet velocity (openfoam f ieldaverage is used for mean values).

14 Results Wind opposing : Vertical profile (at x=210 m) of mean values of the horizontal and vertical component of the wind flow for six cases with different inlet velocity.

15 Results Mean turbulent kinetic energy for wind aligned with the and wind opposing the wave.

16 Results Various wave states opposed with wave propagation. Vertical profile of horizontal wind speed and mean horizontal wind speed.

17 Results Uniform wind of 5 m/s at the inlet. Wave with; c=8 m/s, a=3 m, L=40 m Instant velocity profiles over the wave surface. Lines for every 5 m in the interval of m (over one whole wave length). Wind aligned and wind opposed the wave propagation result in very different response in the wind field.

18 Results Uniform wind of 5 m/s at the inlet. Wave with; c=8 m/s, a=3 m, L=40 m Instant turbulence profiles over the wave surface. Lines for every 5 m in the interval of m (over one whole wave length). Wind aligned and wind opposed the wave propagation result in very different response in the wind field.

19 Results Comparison with Sullivan et al. 2008: A n openfoam URANS setup with a wave with a=1.6 m, L=100 m and c= 12.5 m/s on a domain of 1200 x 100 m is being compared with Sullivan et al s LES simulations. Preliminary results are promising and it looks like we are able to capture the same dynamics as Sullivan et al. But current simulations is to coarse and more refined simulations are needed. Contours of the horizontal wind field for the situation of aligned (top) and opposed with wave propagation (middle), and stationary (bottom). The non-dimensional field shown is mean Ux / Ug.

20 Summary Wave wind simulations with openfoam is on going PhD work at University of Stavanger /StormGeo/Norcowe. A cost efficient CFD method for flow over wave simulations, based on RANS turbulence closure is developed. The response in the boundary layer over the wave are very different for cases where the wind is aligned with the wave propagation and wind opposing the wave. Case of U=5 m/s and c=10 m/s wave: A low level speed up is created in the lowest meters for wind aligned with a fast moving wave. The profiles over the wave do not exhibit a logarithmic profile (or power law profile). Turbulent kinetic energy is slightly higher for wind opposing the wave than wind aligned with the wave. Preliminary result shows pattern that compares well to Sullivan et al. (2008). More detailed studies need to be performed. Next step: Test the significance and the implications of wave-wind interaction on the offshore wind turbine loads and wakes. Wave movement code and turbine modelling code need to be coupled.

21 References Kalvig S, Gundmestad O-T, Winther N. A literature review on implications of wave-influenced wind and atmospheric stability for offshore wind energy. Wind Energy 2013, In press. Kverneland Richard, CFD Simulations of wave-wind interaction, Master theses, University of Stavanger Semedo A, Saetra Ø, Rutgersson A, Kahma KK, Pettersson H. Wave-induced wind in the marine boundary layer. Journal of the Atmospheric Sciences 2009; 66 : Smedman A, Larsén X, Högström U, Kahma K, Petterson H. Effect of sea state on momentum exchange over the sea during neutral conditions. Journal of Geophysical Research 2003; 108, NO.C11, DOI: /2002JC Smedman A, Högström U, Sahlee E, Drennan WM, Kahma KK, Pettersson H, Zhang F. Observational study of marine atmospheric boundary layer characteristics during swell. Journal of the Atmospheric Sciences 2009; 66(9) : DOI: /2009JAS Sullivan PP, Edson JB, Hristov T, McWilliams JC. Large-eddy simulations and observations of atmospheric marine boundary layers above nonequilibrium surface. Journal of the Atmospheric Sciences 2008; 65(4) : Vincent, C. L., P. Pinson, et al. (2011). "Wind fluctuations over the North Sea." International Journal of Climatology 31(11): Acknowledgements; Eirik Manger, Acona Flow Technology OpenCFD, academic support agreement /

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