Richard J.A.M. Stevens

Professor at the University of Twente

Wind energy · Turbulence · Environmental flows

Publication 50 · Wind-farm flow

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).

Read the article Open-access version

Main finding

Mean advection transports velocity correlations while large-scale random sweeping progressively decorrelates them in the wind-farm model. Independent spatial correlations and parameters are still needed for a self-contained prediction.

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 (read the finding), random-sweeping work, and the shared periodic-array LES lineage. Turbulence coherence in wind farms (read the finding) later tests a related coherence closure and shows turbine-operating-state limits.

View in the complete publication list Related wind-farm research