17 Dec 2021
 | 17 Dec 2021
Status: a revised version of this preprint is currently under review for the journal WES.

Applying a Random Time Mapping to Mann modelled turbulence for the generation of intermittent wind fields

Khaled Yassin, Arne Helms, Daniela Moreno, Hassan Kassem, Leo Höning, and Laura J. Lukassen

Abstract. A new approach to derive a synthetic wind field model which combines spatial correlations from the Mann model and intermittency is introduced. The term intermittency describes the transition from Gaussian to non-Gaussian velocity increment statistics at small scales, where non-Gaussian velocity increment statistics imply a higher probability for extreme values than a Gaussian distribution. The presented new model is named the Time-mapped Mann model. The intermittency is introduced by applying a special random time-mapping procedure to the regular Mann model. The Time-mapping procedure is based on the so-called Continuous-time random walk model. As will be shown, the new Time-mapped Mann field reflects spatial correlations from the Mann model in the plane perpendicular to flow direction and temporal intermittency. In a first wind turbine study, the new Time-mapped Mann field and a regular Mann field are used as inflow to a wind turbine in a Blade Element Momentum simulation. It is shown that the wind field intermittency carries over to the loads of the wind turbine, and, thus, shows the importance of carefully modeling synthetic wind fields.

Khaled Yassin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-139', Anonymous Referee #1, 13 Jan 2022
    • AC1: 'Reply on RC1', Khaled Yassin, 24 Mar 2022
  • RC2: 'Comment on wes-2021-139', Anonymous Referee #2, 17 Jan 2022
    • AC2: 'Reply on RC2', Khaled Yassin, 24 Mar 2022

Khaled Yassin et al.

Khaled Yassin et al.


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Short summary
The current turbulent wind field models stated in the IEC 61400-1 standard underestimate the probability of extreme changes in wind velocity. This underestimation can lead to the false calculation of extreme and fatigue loads on the turbine. In this work, we are trying to apply a random time-mapping technique to one of the standard turbulence models to adapt to such extreme changes. The turbulent fields generated are compared with a standard wind field to show the effects of this new mapping.