On interactions between wind turbines and the marine boundary layer

Most mesoscale models are developed with grid resolution in the range of kilometers. Therefore, they may require spatial averaging to analyze flow behavior over the domain of interest. In doing so, certain important features of sub-grid scales are lost. Moreover, spatial averaging on the governing equations results in additional terms known as dispersive fluxes. These fluxes are ignored in the analysis. The aim of this paper is to identify the significance of these fluxes for accurate assessment of flow fields related to wind farm applications. The research objectives are hence twofold: 1) to quantify the impact of wind turbines on MBL characteristics. 2) to account for the magnitude of dispersive fluxes arising from spatial averaging and make a comparison against the turbulent flux values. To conduct the numerical study the NREL 5MW reference wind turbine model is employed with a RANS approach using k-ε turbulence model. The results are presented concerning spatially averaged velocity, wake deficit behind the turbine, dispersive and turbulent fluxes. ∗Address all correspondence to this author. . NOMENCLATURE ρ Density(kg/m3) zo Surface roughness Ω Angular rotation rate(rad/sec) ui Spatially filtered velocity in tensor form(m/s) u ′ Fluctuation in velocity with time(m/s) CFD Computational Fluid Dynamics RANS Reynolds Averaged Navier Stokes BEM Blade Element Momentum LES Large Eddy Simulation MBL Marine Boundary Layer NREL National Renewable Energy Laboratories INTRODUCTION With the size of operational offshore wind turbines increasing rapidly and already in the range of 100–150m, modeling of 1 Copyright © 2017 ASME Proceedings of the ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering OMAE2017 June 25-30, 2017, Trondheim, Norway

[1]  Fernando Porté-Agel,et al.  Large-eddy simulation of atmospheric boundary layer flow through wind turbines and wind farms , 2011 .

[2]  A. Rasheed,et al.  Characterization of Dispersive Fluxes in Mesoscale Models Using LES of Flow over an Array of Cubes , 2013 .

[3]  I. Akhtar,et al.  Quantification of the effects of geometric approximations on the performance of a vertical axis wind turbine , 2015 .

[4]  M. Salman Siddiqui,et al.  Numerical Study to Quantify the Effects of Struts and Central Hub on the Performance of a Three Dimensional Vertical Axis Wind Turbine Using Sliding Mesh , 2013 .

[5]  Trond Kvamsdal,et al.  Numerical Modeling Framework for Wind Turbine Analysis & Atmospheric Boundary Layer Interaction , 2017 .

[6]  Yuri Bazilevs,et al.  Fluid–structure interaction modeling of wind turbines: simulating the full machine , 2012, Computational Mechanics.

[7]  Alberto Martilli,et al.  CFD simulation of airflow over a regular array of cubes. Part II: analysis of spatial average properties , 2007 .

[8]  J. Jonkman,et al.  Definition of a 5-MW Reference Wind Turbine for Offshore System Development , 2009 .

[9]  Trond Kvamsdal,et al.  Investigation of the Impact of Wakes and Stratification on the Performance of an Onshore Wind Farm , 2015 .

[10]  Fernando Porté-Agel,et al.  Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm , 2015 .

[11]  Yuri Bazilevs,et al.  3D simulation of wind turbine rotors at full scale. Part I: Geometry modeling and aerodynamics , 2011 .

[12]  M. Salman Siddiqui,et al.  Numerical Analysis of NREL 5MW Wind Turbine: A Study Towards a Better Understanding of Wake Characteristic and Torque Generation Mechanism , 2016 .

[13]  Harish Gopalan,et al.  A coupled mesoscale–microscale framework for wind resource estimation and farm aerodynamics , 2014 .

[14]  Fue-Sang Lien,et al.  A comparison of large Eddy simulations with a standard k–ε Reynolds-averaged Navier–Stokes model for the prediction of a fully developed turbulent flow over a matrix of cubes , 2003 .

[15]  Hrvoje Jasak,et al.  Dynamic Mesh Handling in OpenFOAM , 2009 .