Two-scale interaction of wake and blockage effects in large wind farms
Two-scale interaction of wake and blockage effects in large wind farms
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大型风电场尾流与阻塞效应的两尺度交互作用
DOI:
10.1017/jfm.2022.979
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发表时间:
2022
影响因子:
3.7
通讯作者:
Kirby A
中科院分区:
文献类型:
--
作者:
Kirby A
Turbine wake and farm blockage effects may significantly impact the power produced by large wind farms. In this study, we perform large-eddy simulations (LES) of 50 infinitely large offshore wind farms with different turbine layouts and wind directions. The LES results are combined with the two-scale momentum theory (Nishino & Dunstan, J. Fluid Mech., vol. 894, 2020, p. A2) to investigate the aerodynamic performance of large but finite-sized farms as well. The power of infinitely large farms is found to be a strong function of the array density, whereas the power of large finite-sized farms depends on both the array density and turbine layout. An analytical model derived from the two-scale momentum theory predicts the impact of array density very well for all 50 farms investigated and can therefore be used as an upper limit to farm performance. We also propose a new method to quantify turbine-scale losses (due to turbine–wake interactions) and farm-scale losses (due to the reduction of farm-average wind speed). They both depend on the strength of atmospheric response to the farm, and our results suggest that, for large offshore wind farms, the farm-scale losses are typically more than twice as large as the turbine-scale losses. This is found to be due to a two-scale interaction between turbine wake and farm induction effects, explaining why the impact of turbine layout on farm power varies with the strength of atmospheric response.
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DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
Oliver Maas;S. Raasch
通讯作者:
S. Raasch
DOI:
10.1088/1742-6596/625/1/012010
发表时间:
2015
期刊:
Journal of Physics: Conference Series
影响因子:
--
作者:
T. Nishino;S. Draper
通讯作者:
S. Draper
DOI:
--
发表时间:
2013
期刊:
影响因子:
--
作者:
C. Archer;S. Mirzaeisefat;Sang Lee
通讯作者:
Sang Lee
影响因子:
3.7
作者:
T. Nishino;T. Dunstan
通讯作者:
T. Dunstan
DOI:
--
发表时间:
2016
期刊:
影响因子:
--
作者:
T. Nishino
通讯作者:
T. Nishino