4th Symposium on OpenFOAM in Wind EnergyMay 2–4, 2016, Delft, the Netherlands

LES modeling of a scaled wind farm facilityin a boundary layer wind tunnel

Jiangang Wang∗

Wind Energy Institute, Technische Universitat Munchen, Boltzmannstraße 15, D-85748 Garching bei Munchen, Germany

Carlo L. BottassoWind Energy Institute, Technische Universitat Munchen, Boltzmannstraße 15, D-85748 Garching bei Munchen, Germany

Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Via La Masa 34, I-20156 Milano, Italy

The Wind Energy Institute at Technische Universitat Munchen has developed a scaled experimental facility for thesimulation of wind turbines and wind farms in a boundary layer wind tunnel. This unique facility enables the con-duction of experiments in aeroservoelasticity, the study of wakes, machine-to-machine interactions, and wind farmcontrol for power maximization and load mitigation. The facility is highly instrumented, allowing for the collectionof a wide range of high quality data, both regarding the flow conditions and the response of the machines. The experi-mental setup is highly flexible, allowing for different machine configurations, operational scenarios, and the testing ofdifferent control algorithms used onboard the individual wind turbines or the whole wind farm. The scaled wind farmfacility is typically operated in the large boundary layer wind tunnel of the Politecnico di Milano [1], shown in Fig. 1.An on-going research effort aims at developing a digital copy of the facility, including the wind turbines and the windtunnel. The simulation model is developed within SOWFA [2], a CFD simulation tool developed by NREL and basedon one of the OpenFOAM standard solvers. The current version of the code uses an actuator line method coupled withthe aeroservolastic simulator FAST [3], an immersed boundary (IB) formulation [4] used to model the wind turbinenacelle and tower, and a wind farm super-controller that manages the cooperative control of the wind turbines [5].

Figure 1: At left, wind tunnel layout; at right, example of setup comprising six individually controller G1 windturbines.

1 MethodsComputational efficiency is of primary importance in the current application, as typical wind farm control tests includedozens of different operating conditions. The solver is derived from the standard implementation named buoyant-BoussinesqPimpleFoam in the OpenFOAM repository. LES turbulence modeling is employed to accurately simulate

∗Ph.D. Candidate, jesse.wang@tum.de.

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4th Symposium on OpenFOAM in Wind EnergyMay 2–4, 2016, Delft, the Netherlands

the far wake behavior. Parameters for the actuator line method were tuned by trial and error to improve accuracy. Liftand drag characteristics of the airfoils are interpolated to account for the local Reynolds number effects. Simulationsare conducted using a second order discretization scheme with the preconditioned conjugate gradient (PCG) linearsolver. Instead of fully resolving all boundary layers, which would imply prohibitive costs, wall functions are used atthe wind tunnel walls and wind turbine boundaries. Turbulence is generated in the wind tunnel with triangular obsta-cles (spires) placed at the test section inlet. The eddies generated by the obstacles break down in their downstreamtravel, generating a sheared flow with desired turbulence intensity and spectrum. This process is modeled numericallyby meshing the inlet section and the spires separately from the wind turbines, so as to be reusable for different windturbine setups and operating conditions. The solver has been augmented with an IB formulation, so that the nacelleand tower of the wind turbine models can be properly modeled. In fact, it was observed that both nacelle and towermay significantly affect the wake development when compared to the isolated rotor case.

2 Results and outlookSimulations show reasonable agreement with experimental measurements, while computational costs are relatively low(approximately 2.4 hours per physical second, using 20 processors on a HPC system). Fig. 2 shows a visualization forone of the test cases studied so far. Various quantities such as power, thrust, loads etc., were post-processed, comparedand analyzed with the experiments. In addition, measurements of the wake were performed in the experiments usinghot wire probes, yielding flow speed and turbulence intensity at various planes behind the wind turbines for a varietyof different operating conditions, results of which are also being compared to the simulations. Although the workis still in progress, we foresee that simulations conducted with the present tool could be used to optimize the testingcampaign. In addition, a validated numerical tool could be used to fill in test point matrices, with considerable potentialsavings in wind tunnel testing time.

Figure 2: Instantaneous velocity plot for three aligned scaled wind turbines.

References[1] Katarina David, Jenele Gorham, Sarah Kim, Patrick Miller, and Carl Minkus. Aeronautical wind tunnels, europe

and asia. DTIC Document, 2006.

[2] M Churchfield and S Lee. Nwtc design codes-sowfa. URL: http://wind. nrel. gov/designcodes/simulator s/SOWFA,2012.

[3] JM Jonkman and Marshall LB Buhl. Fast users guide nrel. Technical report, EL-500-29798, National RenewableEnergy Laboratory, Golden, CO, 2004.

[4] Hrvoje Jasak, Damir Rigler, and Zeljko Tukovic. Finite volume immersed boundary method for turbulent flowsimulations. In 9th OpenFOAM Workshop, 2014.

[5] Paul Fleming, Pieter Gebraad, Jan-Willem van Wingerden, Sang Lee, Matt Churchfield, Andrew Scholbrock, JohnMichalakes, Kathryn Johnson, and Pat Moriarty. The sowfa super-controller: A high-fidelity tool for evaluatingwind plant control approaches. In Proceedings of the EWEA Annual Meeting, Vienna, Austria, 2013.

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