Wind-Turbine and Wind-Farm Flows: A Review

By Fernando Port'e-Agel, M. Bastankhah, Sina Shamsoddin. Boundary-layer Meteorology, 2019

943 citations recorded by the source corpus.

Wind energy, together with other renewable energy sources, are expected to grow substantially in the coming decades and play a key role in mitigating climate change and achieving energy sustainability. One of the main challenges in optimizing the design, operation, control, and grid integration of wind farms is the prediction of their performance, owing to the complex multiscale two-way interactions between wind farms and the turbulent atmospheric boundary layer (ABL). From a fluid mechanical perspective, these interactions are complicated by the high Reynolds number of the ABL flow, its inherent unsteadiness due to the diurnal cycle and synoptic-forcing variability, the ubiquitous nature of thermal effects, and the heterogeneity of the terrain. Particularly important is the effect of ABL turbulence on wind-turbine wake flows and their superposition, as they are responsible for considerable turbine power losses and fatigue loads in wind farms. These flow interactions affect, in turn, the structure of the ABL and the turbulent fluxes of momentum and scalars. This review summarizes recent experimental, computational, and theoretical research efforts that have contributed to improving our understanding and ability to predict the interactions of ABL flow with wind turbines and wind farms.

Subfields: Aerospace Engineering, Computational Mechanics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/015ec0a090316f565dee41e7fa879048d47cb6ae

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Citations in the corpus

Towards optimal layout design of vertical-axis wind-turbine farms: Double rotor arrangements (2020, background): “[3], Stevens and Meneveau [13] and Porté-Agel [14].”
A momentum-conserving wake superposition method for wind farm power prediction (2020, methodology): “…(either local or global) and the operations adopted to combine the wakes (either summing the wake velocity deficits, or summing the squares of the wake velocity deficits), four wake superposition methods are available in the literature (Stevens & Meneveau 2017; Porté-Agel et al. 2019), as follows.”