Open AccessOn Stochastic Reduced-Order and LES-based Models of Offshore Wind Turbine Wakes
Author(s) -
Mostafa Bakhoday Paskyabi,
Maria Krutova,
Finn Gunnar Nielsen,
Joachim Reuder,
Omar El Guernaoui
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1669/1/012018
Subject(s) - turbine , dynamic mode decomposition , weighting , wake , flow (mathematics) , offshore wind power , wind power , mathematics , computer science , control theory (sociology) , engineering , physics , mechanics , geometry , aerospace engineering , electrical engineering , control (management) , artificial intelligence , acoustics
In this paper, the primary objective is to investigate flow structures in the wake of wind turbines based on applying a truncated Proper Orthogonal Decomposition (POD) approach. This scheme decomposes the three-dimensional velocity fields produced by the high-fidelity PArallelized LES Model (PALM) into a number of orthogonal spatial modes and time-dependent weighting coefficients. PALM has been combined with an actuator disk model with rotation to incorporate the effects of a turbine array. The time-dependent deterministic weights from applying the POD scheme are replaced by stochastic weights, estimated from two independent stochastic techniques that aim to account for unresolved small-scale features for a number of POD modes. We then reconstruct the flow field by a small number of stochastic modes to investigate how well the applied stochastic methodologies can reproduce the flow field compared to the original LES results.