Michael J. LoCascio
FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization
LoCascio, Michael J.; Bay, Christopher J.; Martínez‐Tossas, Luis A.; Bastankhah, Majid; Gorlé, Catherine
Authors
Christopher J. Bay
Luis A. Martínez‐Tossas
Dr Majid Bastankhah majid.bastankhah@durham.ac.uk
Associate Professor
Catherine Gorlé
Abstract
Annual energy production (AEP) is commonly used in objective functions for wind farm layout optimization. AEP is proportional to wind farm power production integrated over an annual distribution of free‐stream wind conditions. Physics‐based estimates of wind farm power production typically rely on low‐fidelity engineering wake models that approximate the steady‐state wind farm flow field. AEP estimates are then obtained by performing independent simulations for discrete wind conditions and using rectangular quadrature to account for each condition's expected frequency of occurrence. Depending on the number of simulated discrete wind conditions, this numerical integral could be hampered by poor accuracy or high computational costs. The FLOWERS AEP model instead poses an analytical integral of the engineering wake model over the variable wind conditions, yielding a closed‐form, analytical function for wind farm AEP. This paper derives the analytical functions for FLOWERS AEP and its derivatives with respect to turbine position, which are useful for gradient‐based wind farm layout optimization, in nondimensional form. We then analyze the benefits of the FLOWERS AEP model over conventional reference models, focusing on its low cost, adequate wake loss predictions, and smooth design space. Although the FLOWERS approach is found to predict the exact value of AEP with some error relative to the reference model (within 14% on average), it dramatically reduces computation time by an order of magnitude, produces a qualitatively similar design space at relatively low resolution, and yields comparable optimal layouts. This significant speed improvement is critical in layout optimization applications, where determining an optimal layout in an efficient manner is more important than precise AEP prediction.
Citation
LoCascio, M. J., Bay, C. J., Martínez‐Tossas, L. A., Bastankhah, M., & Gorlé, C. (online). FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization. Wind Energy, Article e2954. https://doi.org/10.1002/we.2954
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 1, 2024 |
Online Publication Date | Oct 27, 2024 |
Deposit Date | Nov 5, 2024 |
Publicly Available Date | Nov 5, 2024 |
Journal | Wind Energy |
Print ISSN | 1095-4244 |
Electronic ISSN | 1099-1824 |
Publisher | Wiley Open Access |
Peer Reviewed | Peer Reviewed |
Article Number | e2954 |
DOI | https://doi.org/10.1002/we.2954 |
Keywords | annual energy production, wake modeling, wind farm layout optimization |
Public URL | https://durham-repository.worktribe.com/output/3043766 |
Files
Published Journal Article (Advance Online Version)
(15.1 Mb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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