A reference database for the analysis of wind-farm wake recovery mechanisms in a large-eddy simulation framework, capping-inversion heights=500 m, capping-inversion strength=8 K, free-atmosphere lapse rate=8 K/km

For a capping-inversion heights=500 m, capping-inversion strength=8 K, free-atmosphere lapse rate=8 K/km, we present a suite of large-eddy simulations of a wind farm operating in conventionally neutral atmospheric boundary layers (CNBLs). A fixed 1.6 GW wind farm is considered for 40 different atmospheric stratification conditions to investigate effects on wind-farm efficiency and blockage, as well as related gravity-wave excitation. A tuned Rayleigh damping layer and a wave-free fringe region method (Lanzilao & Meyers, Bound. Layer Meteor. 186, 2023) are used to avoid spurious excitation of gravity waves, and a domain-size study is included to evaluate and minimize effects of artificial domain blockage. A fully neutral reference case is also considered, to distinguish between a case with hydrodynamic blockage only, and cases that include hydrostatic blockage excited by gravity waves. We discuss in detail the dependence of gravity-wave excitation, flow fields, and wind-farm blockage on capping-inversion height, strength and free-atmosphere lapse rate. In all cases, an unfavourable pressure gradient is present in front of the farm, and a favourable pressure gradient in the farm, with hydrostatic contributions arising from gravity waves at least an order of magnitude larger than hydrodynamic effects. Using respectively non-local and wake efficiencies nu_{nl} and nu_w (Allaerts & Meyers, Bound. Layer Meteor. 166, 2018), we observe a strong negative correlation between unfavourable upstream pressure rise and nu_{nl}, and a strong positive correlation between the favourable pressure drop in the farm and nu_w. Using a simplified linear gravity-wave model, we formulate a simple scaling for nu_{nl}/nu_w, which matches reasonably well with the LES results.

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Source https://doi.org/10.48804/L45LTT
Version 1.0
ရေးသားသူ L. Lanzilao, J. Meyers
ထိန်းသိမ်းသူ J. Meyers
ထိန်းသိမ်းသူ၏ email လိပ်စာ J. Meyers
Dataset subject Wind Farm,Wakes
External conditions Flat Terrain,offshore
Dataset variables wind_speed,wind_direction,air_temperature
Spatial Data