LAPSE:2023.27779
Published Article
LAPSE:2023.27779
A Steady-State Wind Farm Wake Model Implemented in OpenFAST
April 11, 2023
Abstract
Wake models play a fundamental role in finding optimized solutions in wind farm control. In fact, they allow assessing how wakes develop and interact with each other with the agility required for real-time applications. In this paper, a Gaussian Wake Model (GWM) is implemented in the OpenFAST framework in a way such that its fidelity is increased with respect to previously implemented models, while enhancing its compatibility with control purposes. The OpenFAST tool is coupled with Floris, NREL’s software based on the GWM, in order to simulate the wake effect on downstream machines (in the case where the downstream rotor is fully covered by the wake, only partially covered by the wake, of the wake is generated by the interaction of more than one turbine), while the rotor aerodynamics is calculated using the BEMT on the actual rotor flow field. We intend this work as a starting point for developing and testing open/closed-loop control logics that will work in real wind farms. To show the suitability of the implementation, the entire model is then compared to Floris.
Keywords
Floris, Gaussian wake model, OpenFAST, wake model, wind farm control, wind turbine
Suggested Citation
Cioffi A, Muscari C, Schito P, Zasso A. A Steady-State Wind Farm Wake Model Implemented in OpenFAST. (2023). LAPSE:2023.27779
Author Affiliations
Cioffi A: Department of Mechanical Engineering, Politecnico di Milano, 20156 Milano, Italy [ORCID]
Muscari C: Department of Mechanical Engineering, Politecnico di Milano, 20156 Milano, Italy [ORCID]
Schito P: Department of Mechanical Engineering, Politecnico di Milano, 20156 Milano, Italy [ORCID]
Zasso A: Department of Mechanical Engineering, Politecnico di Milano, 20156 Milano, Italy [ORCID]
Journal Name
Energies
Volume
13
Issue
23
Article Number
E6158
Year
2020
Publication Date
2020-11-24
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en13236158, Publication Type: Journal Article
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LAPSE:2023.27779
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https://doi.org/10.3390/en13236158
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