Parameterized Vertical-Axis Wind Turbine Wake Model Using CFD Vorticity Data
Author(s) -
Eric Tingey,
Andrew Ning
Publication year - 2016
Publication title -
scholarsarchive (brigham young university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2016-1730
Subject(s) - wake , computational fluid dynamics , turbine , vorticity , solidity , wind speed , meteorology , mechanics , vertical axis wind turbine , parameterized complexity , wind power , marine engineering , environmental science , physics , computer science , aerospace engineering , vortex , engineering , electrical engineering , algorithm , programming language
In order to analyze or optimize a wind farm layout, reduced-order wake models are often used to estimate the interactions between turbines. While many such models exist for horizontal-axis wind turbines, for vertical-axis wind turbines (VAWTs) a simple parametric wake model does not exist. Using computational fluid dynamic (CFD) simulations we computed vorticity in a VAWT wake, and parameterized the data based on normalized downstream positions, tip-speed ratio, and solidity to predict a normalized wake velocity deficit. When compared to CFD, which takes about a day to run one simulation, the reduced-order model predicts the velocity deficit at any location within 5-6% accuracy in a matter of milliseconds. The model was also found to agree well with trends observed in experimental data. Future additions will allow the reduced-order model to be used in wind farm layout analysis and optimization by accounting for multiple wake interactions.
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