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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 29 Jan 2020

Submitted as: research article | 29 Jan 2020

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This preprint is currently under review for the journal WES.

Evaluation of the Lattice Boltzmann Method for wind modelling in complex terrain

Alain Schubiger, Sarah Barber, and Henrik Nordborg Alain Schubiger et al.
  • University of Applied Sciences Rapperswil (HSR), Oberseestrasse 10, 8640 Rapperswil, Switzerland

Abstract. The worldwide expansion of wind energy is making the choice of potential wind farm locations more and more difficult. This results in an increased number of wind farms being located in complex terrain, which is characterised by flow separation, turbulence and high shear. Accurate modelling of these flow features is key for wind resource assessment in the planning phase, as the exact positioning of the wind turbines has a large effect on their energy production and life time. Wind modelling for wind resource assessments is usually carried out with the linear model WAsP, unless the terrain is complex, in which case Reynolds-Averaged Navier-Stokes (RANS) solvers such as WindSim and ANSYS Fluent are usually applied. Recent research has shown the potential advantages of Large Eddy Simulations (LES) for modelling the atmospheric boundary layer and thermal effects; however, LES is far too computationally expensive to be applied outside the research environment. Another promising approach is the Lattice Boltzmann Method (LBM), a computational fluid technique based on the Boltzmann transport equation. It is generally used to study complex phenomena such as turbulence, because it describes motion at the microscopic level in contrast to the macroscopic level of conventional Computational Fluid Dynamics (CFD) approaches, which solve the Navier-Stokes (N-S) equations. Other advantages of LBM include its efficiency, near ideal scalability on High Performance Computers (HPC) and its ability to easily automate the geometry, the mesh generation and the post-processing of the geometry. However, LBM has not yet been applied to wind modelling in complex terrain for wind energy applications, mainly due to the lack of availability of easy-to-use tools as well as the lack of experience with this technique. In this paper, the capabilities of LBM to model wind flow around complex terrain are investigated using the Palabos framework and data from a measurement campaign from the Bolund Hill experiment in Denmark. Detached Eddy Simulations (DES) and LES in ANSYS Fluent are used as a numerical comparison. The results show that there is in general a good agreement between simulation and experimental data, and LBM performs better than RANS and DES. Some deviations can be observed near the ground, close to the top of cliff and on the lee side of the hill. The computational costs of the three techniques are compared and it has been shown that LBM can perform up to 5 times faster than DES, even though the set-up was not optimised in this initial study. It can be summarised that LBM has a very high potential for modelling wind flow over complex terrain accurately and at relatively low costs, compared to solving the N-S conventionally. Further studies on other sites are ongoing.

Alain Schubiger et al.

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Alain Schubiger et al.

Alain Schubiger et al.


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Short summary
In this study, a LES simulation using the LBM framework Palabos was implemented to calculate the wind field over the complex terrain of the Bolund Hill. The results were compared to RANS and DES simulations using ANSYS Fluent and field measurements. The computational costs of these three models were compared and it has been shown that LBM, even in this not-yet fully optimised set-up of the simulation, can perform 5 times faster than DES and lead to reasonably accurate results.
In this study, a LES simulation using the LBM framework Palabos was implemented to calculate the...