RENEWABLE ENERGY | 卷:136 |
Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions | |
Article | |
Shaler, Kelsey1,3  Kecskemety, Krista M.2  McNamara, Jack J.1  | |
[1] Ohio State Univ, Mech & Aerosp Engn, W19th Ave, Columbus, OH 43210 USA | |
[2] Ohio State Univ, Dept Engn Educ, 244 Hitchcock Hall,2070 Neil Ave, Columbus, OH 43210 USA | |
[3] Natl Renewable Energy Lab, 15013 Denver W Pkwy, Golden, CO USA | |
关键词: Free vortex wake; Turbine-wake interaction; Wake effects; Blade loads; Turbine power; Wake structure; | |
DOI : 10.1016/j.renene.2018.12.044 | |
来源: Elsevier | |
【 摘 要 】
Turbine-wake interactions pose significant challenges in the development of wind farms. These interactions can lead to an increase in wind energy cost through reduction in wind farm power efficiency as well as a reduction of functional turbine lifetime. The overall objective of this work is to assess the free vortex wake (FVW) approach for capturing wind farm interactions in the context of improved wind farm optimization. Specific focus areas include (1) analyzing the effects of turbine-wake interaction and (2) benchmarking of the model against experimental wind farm measurements. The effects of turbine-wake interactions are analyzed in terms of wake structure, rotor power, and structural response. The FVW model predicts increased unsteadiness in wake-influenced turbine rotor power and out-of-plane blade root bending moment. This could have implications for prediction of turbine life and suggests that the transient as well as average response of turbines should be considered to fully capture the effects of wake interaction. Comparisons between the FVW predictions and experimental measurements of relative rotor power are made over varying yaw angle and freestream velocity. Overall trends are predicted by the FVW approach, with less than 13% error on average when compared to wind farm measurements. These results indicate the FVW method is a useful tool for carrying out improved optimization of wind farms. (C) 2019 Elsevier Ltd. All rights reserved.
【 授权许可】
Free
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
10_1016_j_renene_2018_12_044.pdf | 2394KB | download |