Modeling space-time correlations of velocity fluctuations in wind farms

Lukassen, L.J.; Stevens, R.J.A.M.; Meneveau, C.; Wilczek, M.

doi:10.1002/we.2172

Modeling space-time correlations of velocity fluctuations in wind farms

L.J. Lukassen, R.J.A.M. Stevens, C. Meneveau, M. Wilczek, Wind Energy 21 (7), 474-487 (2018).

Main finding

A useful bounded closure and diagnostic, not a self-contained predictor until the spatial correlation and parameters are independently modelled or measured.

Space-time velocity correlation against spatial and temporal separation with model and simulation — **How to read the figure.** The two-point velocity correlation in a wind farm against spatial separation (left) and time separation (right), at five values of the other variable; solid curves are the model, dotted the large-eddy simulation. The peaks fall and broaden as separation grows - turbulence loses memory as it is carried downstream. The model closes the correlation given its parameters, so it is a bounded diagnostic rather than a self-contained predictor until those parameters are measured independently. Open the full-resolution figure. Figure 7. L.J. Lukassen et al. (2018). No separate licence is stated here; consult the original publication and credited source before reuse.

Why this matters

Velocity correlations are advected by the mean flow and progressively decorrelated by large-scale random sweeping.

Research context

Builds on Flow Structure and Turbulence in Wind Farms, random-sweeping work, and the shared periodic-array LES lineage. Turbulence coherence in wind farms later tests a related coherence closure and shows turbine-operating-state limits.

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