Leverage the latest IT methods to enhance wind flow modeling processes

Introduction

The global wind industry has become more mature and sophisticated in the past half-decade, with a much better understanding of wind farm modeling at multiple scales. However, the lack of calculation power still seriously affects the output quality of wind simulations as wind engineers often have to compromise on accuracy in order to be able to deliver results based on tight project timelines. Thanks to on-demand elastic cloud computing and opensource solvers (WRF and OpenFOAM), all the wind simulation jobs can be run at the same time on powerful servers so that engineers are left with more time to tune models and to improve accuracy. CFD-based case studies on projects located on complex sites in Europe and Asia show that accuracy is a growing function of calculation power.

Approach

Deploying simultaneously open source CFD solvers on an unlimited number of elastic cloud servers allow getting almost instant results with no limitation in number of cells (i.e. resolutions), number of directional runs and number of solver iterations.

Main body of abstract

CFD-based assessments carried out on several wind projects located on complex sites in Europe and Asia show that increasing the model resolution, increasing the number of solver iterations, and increasing the number of calculated directions can lead to more accurate results. Dividing the calculation time also allows in-depth analyses such as horizontal and vertical mesh discretization sensitivity analyses, vertical profiles calibration, cross-extrapolations and convergence control. This study is the first step towards a model allowing quantifying wind modeling uncertainties by performing automatic sensitivity analyses on modeling inputs.

Conclusion

Open Source solvers and Cloud Computing capabilities can be leveraged to address the most advanced wind flow modeling requirements and deliver more accurate results. This study is the first step towards a model allowing quantifying wind modeling uncertainties.


Learning objectives
1/ One of the main limitation towards more accurate wind simulations is the lack of calculation power.
2/ Without the limitation of calculation power, more accurate results can be delivered and more time can be allocated for analyses based on best practices.