ECCOMAS Congress 2016 VII European Congress on Computational Methods in Applied Sciences and Engineering M. Papadrakakis, V. Papadopoulos, G. Stefanou, V. Plevris (eds.) Crete Island, Greece, 5–10 June 2016 COUPLED UNSTEADY OPENFOAM AND WRF SOLUTIONS FOR AN ACCURATE ESTIMATION OF WIND ENERGY POTENTIAL Engin Leblebici 1 and Ismail H. Tuncer 1 1 GRA at Aerospace Engineering Dept., [email protected]2 Prof. at Aerospace Engineering Dept., [email protected]Middle East Technical University, Ankara, TURKEY Keywords: Computational Fluid Dynamics, Wind Energy, Power Prediction, OpenFOAM, WRF Abstract. The objective of the this study is the development of a high fidelity tool to estimate short term wind energy production potential accurately for a region of interest. For that pur- pose, the mesoscale weather prediction model WRF (Weather Research and Forecast) is coupled with the open source flow solver OpenFOAM. The coupling is achieved by applying the low res- olution WRF solution as the spatially varying, unsteady boundary condition in OpenFOAM. Coupled WRF and OpenFOAM solutions are performed in Mersin/Mut region in Turkey where a wind-farm and a met-mast are located. The laminar flow fields obtained in the preliminary study successfully validate the method developed. 1
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ECCOMAS Congress 2016VII European Congress on Computational Methods in Applied Sciences and Engineering
M. Papadrakakis, V. Papadopoulos, G. Stefanou, V. Plevris (eds.)Crete Island, Greece, 5–10 June 2016
COUPLED UNSTEADY OPENFOAM AND WRF SOLUTIONS FOR ANACCURATE ESTIMATION OF WIND ENERGY POTENTIAL
Keywords: Computational Fluid Dynamics, Wind Energy, Power Prediction, OpenFOAM,WRF
Abstract. The objective of the this study is the development of a high fidelity tool to estimateshort term wind energy production potential accurately for a region of interest. For that pur-pose, the mesoscale weather prediction model WRF (Weather Research and Forecast) is coupledwith the open source flow solver OpenFOAM. The coupling is achieved by applying the low res-olution WRF solution as the spatially varying, unsteady boundary condition in OpenFOAM.Coupled WRF and OpenFOAM solutions are performed in Mersin/Mut region in Turkey wherea wind-farm and a met-mast are located. The laminar flow fields obtained in the preliminarystudy successfully validate the method developed.
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1 INTRODUCTION
Since wind farms with a large number of wind turbines have a high initial investment cost,wind farm siting must be given a significant importance. [1, 2] Low resolution wind energypotential atlases have the necessary statistical information for macro-siting of wind farms butlack the precision for the micro-siting. Therefore; high resolution, more accurate wind fieldinformation may be needed for micro-siting in order to improve the power output of a wind-farm.
Bowen(2004)[3] in a Riso-R Report states that Botta et al (1992)[4], Bowen and Saba(1995)[5], Reid (1995)[6] and Sempreviva et al (1986)[7] experiences in the operation of com-mercial wind farms [8] have confirmed that effects from the local complex terrain on the sitecharacteristics of each turbine have a significant influence on the output (and perhaps even theviability) of a wind energy project. F.J.Zajaczkowski [9] compares Numerical Weather Predic-tion Models (NWP) and Computational Fluid Dynamics (CFD) simulations. They concludethat NWP can take radiation, moist convection physics, land surface parametrization, atmo-spheric boundary layer physics closures, and other physics into account, but wind flow featuresfiner than 1 km are not captured by the turbulence physics of such models. CFD simulations,however, have proved to be useful at capturing the details of smaller scales due to a finer scaletopography, and details around urban features such as high-rise buildings. Most of the commer-cial wind power prediction tools either use statistical methods or linearized computational fluiddynamics (CFD) models. The linearized models use fictitious flow fields that are created by as-suming uniform inflow conditions from various wind directions (Figure 1), and interpolate thesesolutions to reconstruct flow fields based on the observation data. Because of the uniformity ofthe boundary conditions and absence of time dependency in linearized CFD models, most ofthe commercial wind power prediction tools cannot answer the question how much energy canbe extracted tomorrow? which is a valuable information for the energy market.
WRF is a fully compressible, Eulerian, η coordinate based, nest-able, non-hydrostatic, nu-merical weather prediction model with a large suite of options for numerical schemes andparametrization of physical processes [10]. WRF uses latitude longitude (horizontal) and η(vertical)coordinate which models altitude as non-dimensional pressure levels. Usage of η co-ordinate degrades the terrain resolution as seen in Figure 2.
Figure 1: Linearized CFD models BC Figure 2: η Coordinate system in WRF
The OpenFOAM (Open Field Operation and Manipulation) CFD Toolbox is a free, opensource CFD software package which has an extensive range of features to solve anything fromcomplex fluid flows involving chemical reactions, turbulence and heat transfer, to solid dynam-ics and electromagnetics.[11]
In this study, the mesoscale weather prediction model WRF (Weather Research and Forecast)
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is coupled with the open-source Navier-Stokes solver OpenFOAM via using low resolutionWRF data as unsteady and spatially varying boundary conditions in OpenFOAM.
2 METHOD
In this study, a coupled flow solution methodology with an atmospheric weather forecastsoftware, WRF, and OPENFOAM, an open source Navier-Stokes solver, is developed. WRFproduces a low resolution, unsteady atmospheric weather forecast data, which provides theunsteady and spatially varying boundary conditions for the flow solutions obtained with OPEN-FOAM on terrain fitted, high resolution unstructured grids.
Figure 3: WRF and OpenFOAM solution domains Figure 4: Structured grid for OpenFOAM
Unsteady WRF solutions are first obtained over the geographical domain of interest which isMersin-Mut in Turkey. The local terrain data is downloaded automatically from UCAR (Uni-versity Corporation of Atmospheric Research) server via WRF. The time dependent initial andboundary conditions for the WRF solution are obtained from ECMWF (European Centre ofMedium Range Weather Forecast). WRF has a 1/3 nesting ratio for downscaling and thus theparent domain has 3 km resolution whereas the nested domain has 1 km. The unsteady bound-ary conditions needed for the OPENFOAM solution at its domain boundaries, which fall intothe nested WRF domain, are then extracted from the WRF solutions at 5 minute time intervals.The nested WRF solution domain and the OpenFOAM domain are given in Figure 3
In the generation of computational grids for the OpenFOAM solutions, the high resolutionterrain topography is first constructed using the data obtained from ASTER GDEM, which isa product of METI and NASA, and provide worldwide digital elevation data at 1.5 arc-secresolution which is about 30 meters. A stretched structured grid with 164700 cell is used todiscretize the complex terrain of interest as seen in Figure 4. The terrain fitted grid has ahorizontal resolution of 30 meters and a vertical resolution of 1 meter and stretches in thevertical direction. Such a high resolution grid is employed in order to capture the viscous flowcharacteristics heavily influenced by the terrain features within the atmospheric boundary layerswhere the wind turbines reside.
The spatially and time varying boundary conditions needed for the OpenFOAM solutionare interpolated both in time and space from the WRF solutions and updated for each cell. Aschematic for the coupling procedure is given in Figure 5.
The boundary conditions implemented in the region of interest is modeled as seen in Figure 6.The side and top surfaces are modeled as spatially and time varying velocity inflow/outflowconditions, and the data are extracted from the WRF solutions.
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Figure 5: Coupling WRF with OpenFOAM Figure 6: Boundary conditions for OpenFOAM
The available boundary condition class and the ones inherit that in OpenFOAM only takefixed values for flow variables and can not be used. Therefore a new boundary condition class,derived from InletOutlet boundary condition class which inherits mixedFvPatchField class inOpenFOAM, is developed in this study. In the new class, the inflow velocities at the domainboundaries are imposed as extracted from the WRF solution. Whereas, the velocity gradientsare set to zero at the outflow boundaries in order to satisfy the incompressible conservation ofmass equation in the presence of interpolation errors at the inflow boundaries.
The PimpleFoam module is used as the solver of choice for the unsteady incompressible at-mospheric flow field solutions as the solver is robust for relatively large time steps. PimpleFoamuses Multiple cycling over the same time step using the last iteration final value as initial guessfor the next iteration (outer correction loops) and under-relaxation of the variables between con-sequent outer iterations. The main advantage of the solver is that the time step can be adjustedaccording to the maximum Courant number, reducing instabilities.
3 RESULTS
Unsteady OpenFOAM solutions coupled with WRF are performed on high resolution struc-tured grids using the methodology developed. The region of interest is chosen as Mersin Mutin Turkey where a wind farm and a met-mast is located. The preliminary coupled flow solutionsare obtained for laminar flows. The nested WRF solutions are first obtained for the same simu-lation period using a parent domain of 3 km horizontal resolution and a nest of 1 km resolution.The computations are performed for the date 04.04.2010 starting from 00:00 GMT 0 to 12:00.The parent and the nested solution domains are 100x79 (horizontal) x 50 (vertical) size, and88x67 (horizontal) x 50 (vertical) respectively. Unsteady solutions in the nested domain aresaved in 5 minute time intervals, which are used to provide the unsteady boundary conditionsfor the OpenFOAM solution.
In order to validate the coupling methodology developed, the unsteady OpenFOAM solutionsare first compared with WRF solution at an intermediate solution step as shown in Figure 7 andFigure 8. As seen, at the inflow boundaries velocity magnitudes are in good agreement asexpected. At the outflow boundaries the contour levels indicate that the OpenFOAM solutionslightly overpredicts the velocity magnitude. The velocity vectors at the domain boundaries andinside the domain are given in Figure 9 and Figure 10 at various time steps along the simulation.
The solution with PimpleFoam module could only be obtained at a relatively low CFL num-bers of about 5. The larger CFL numbers caused instabilities and divergence of the solutions.Therefore, the serial computation on a 3.4Ghz Intel CPU takes about 30 hours for a simulation
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OpenFOAM WRF
Figure 7: OpenFOAM vs WRF solutions (Mostly Inflow)
OpenFOAM WRF
Figure 8: OpenFOAM vs WRF solutions (Mostly Outflow)
period of 12 hours. The current study focuses on the CFL limitations and on the developmentof a parallel solution algorithm similarly coupled with the WRF solution.
4 CONCLUSIONS
Unsteady atmospheric flow solutions with OpenFOAM are successfully coupled with WRFsolutions through the implementation of boundary conditions. Preliminary results obtained arevalidated with the WRF solutions, and are promising for an accurate prediction of near groundwind flows. The serial computations with a Courant number of 5 take about 30 hours on a3.4Ghz Intel CPU for a 12 hour simulation. The current study concentrates on the alleviation ofCourant number limitation, and implementation of turbulent flow solutions and parallel solutionalgorithms.
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Figure 9: Unsteady OpenFOAM Solutions Inlet and Outlet Profiles
5 ACKNOWLEDGEMENTS
This work is supported by ”The Scientific And Technological Research Council Of Turkey”(TUBITAK) under the project no: 215M385 and this support is greatly acknowledged.
REFERENCES
[1] R. Damiani, B. Cochran, K. Orwig, J. Peterka, Complex Terrain: A Valid Wind Option?.American Wind Energy Association, 2008.
[2] R.G. Derickson, J.A. Peterka, K. Orwig, J. Peterka, Development of a Powerful HybridTool for Evaluating Wind Power in Complex Terrain: Atmospheric Numerical Models andWind Tunnels. American Institute of Aeronautics and Astronautics, 2004.
[3] Anthony J. Bowen and Niels G. Mortensen, WAsP prediction errors due to site orography.Riso National Laboratory, (Denmark, Roskilde),2004
[4] G. Botta, R. Castagna, M. Borghetti and D. Mantegna, Wind analysis on complex terrain- The case of Acqua Spruzza. Riso National Laboratory, (Denmark, Roskilde),1992
[5] Anthony J. Bowen and T. Saba, The evaluation of software for wind turbine siting in hillyterrain. 9th International Conference on Wind Engineering, India, 1995
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Figure 10: Unsteady OpenFOAM solutions coupled with WRF
[7] A.M. Sempreviva, I. Troen and A. Lavagnini Modelling of wind power potential in Sar-dinia. European Wind Energy Association Conference and Exhibition, (Rome Italy), pp391-6, 1986
[8] D. Lindley, P. Musgrove, J. Warren, R. Hoskin, Operating experience from four UK windfarms. 15th BWEA Annual Wind Energy Conference, (York, UK), p 41-45., 1993
[9] Frank J. Zajaczkowski, Sue Ellen Haupt, Kerrie J. Schmehl A preliminary study of assim-ilating numerical weather prediction data into computational fluid dynamics models forwind prediction. Journal of Wind Engineering and Industrial Aerodynamics 99 pp 320-329., 2011
[10] William C. Skamarock, Joseph B. Klemp, Jimy Dudhia, David O. Gill, Dale M. Barker,Michael G. Duda, Xiang-Yu Huang, Wei Wang, Jordan G. Powers A Description of theAdvanced Research WRF Version 3. National Center for Atmospheric Research, (Boulder,Colorado, USA), 2008
[11] www.openfoam.org/features OpenCFD Ltd. last accessed: 08.04.2016
