Articles | Volume 9, issue 2
https://doi.org/10.5194/wes-9-321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Feb 2024
Research article |
| 07 Feb 2024
| 07 Feb 2024
Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout
Rafael Valotta Rodrigues
CORRESPONDING AUTHOR
Wind and Energy Systems Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
now at: Electrical and Computer Engineering Department, University of Massachusetts Boston, 100 Morissey Blvd, Boston, MA 02125, United States of America
Mads Mølgaard Pedersen
Wind and Energy Systems Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Jens Peter Schøler
Wind and Energy Systems Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Julian Quick
Wind and Energy Systems Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Pierre-Elouan Réthoré
Wind and Energy Systems Department, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
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Cited
15 citations as recorded by crossref.
- Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients M. LoCascio et al. 10.1063/5.0237778
- Gradient-based wind farm layout optimization with inclusion and exclusion zones J. Criado Risco et al. 10.5194/wes-9-585-2024
- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al. 10.1016/j.renene.2025.123657
- Parametric Analysis of Inter-Farm Wake Interactions in Offshore Wind Farm Projects Along the US East Coast A. Moura & R. Rodrigues 10.1088/1742-6596/3016/1/012049
- FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization M. LoCascio et al. 10.1002/we.2954
- A novel circle-packing NLP model for offshore wind farm layout and cable optimization A. Negrete-Romero et al. 10.1016/j.compchemeng.2025.109346
- Benchmarking Engineering Wake Models for Assessing Wind Farm Wakes Interaction R. Rodrigues & A. Moura 10.1088/1742-6596/3016/1/012045
- Prognostic digital twinning of lattice-tubular hybrid wind turbine towers exposed to deterioration T. Zheng et al. 10.1016/j.istruc.2025.109461
- Offshore wind farm layout optimization accounting for participation in secondary reserve markets T. Nguyen et al. 10.5194/wes-10-1661-2025
- Gradient Descent Algorithm with Greedy Repositioning Using Power Deficit Aggregation of Wakes to Accelerate the Offshore Wind Farm Layout Optimization Problem in Irregular Concession Areas A. Gonzalez-Rodriguez et al. 10.3390/app142311331
- Discrete bi-population differential evolution for optimizing complex wind farm layouts in diverse terrains J. Li et al. 10.1016/j.energy.2025.137885
- Identifying interaction patterns to speed-up the AEP evaluation in large offshore wind farms with uniformly distributed turbines and exclusion zones A. Gonzalez-Rodriguez et al. 10.1016/j.renene.2025.123445
- Leveraging Quantum Annealing for Layout Optimization L. Nigro et al. 10.1002/qute.202500358
- Stochastic gradient descent for wind farm optimization J. Quick et al. 10.5194/wes-8-1235-2023
- Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout R. Valotta Rodrigues et al. 10.5194/wes-9-321-2024
13 citations as recorded by crossref.
- Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients M. LoCascio et al. 10.1063/5.0237778
- Gradient-based wind farm layout optimization with inclusion and exclusion zones J. Criado Risco et al. 10.5194/wes-9-585-2024
- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al. 10.1016/j.renene.2025.123657
- Parametric Analysis of Inter-Farm Wake Interactions in Offshore Wind Farm Projects Along the US East Coast A. Moura & R. Rodrigues 10.1088/1742-6596/3016/1/012049
- FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization M. LoCascio et al. 10.1002/we.2954
- A novel circle-packing NLP model for offshore wind farm layout and cable optimization A. Negrete-Romero et al. 10.1016/j.compchemeng.2025.109346
- Benchmarking Engineering Wake Models for Assessing Wind Farm Wakes Interaction R. Rodrigues & A. Moura 10.1088/1742-6596/3016/1/012045
- Prognostic digital twinning of lattice-tubular hybrid wind turbine towers exposed to deterioration T. Zheng et al. 10.1016/j.istruc.2025.109461
- Offshore wind farm layout optimization accounting for participation in secondary reserve markets T. Nguyen et al. 10.5194/wes-10-1661-2025
- Gradient Descent Algorithm with Greedy Repositioning Using Power Deficit Aggregation of Wakes to Accelerate the Offshore Wind Farm Layout Optimization Problem in Irregular Concession Areas A. Gonzalez-Rodriguez et al. 10.3390/app142311331
- Discrete bi-population differential evolution for optimizing complex wind farm layouts in diverse terrains J. Li et al. 10.1016/j.energy.2025.137885
- Identifying interaction patterns to speed-up the AEP evaluation in large offshore wind farms with uniformly distributed turbines and exclusion zones A. Gonzalez-Rodriguez et al. 10.1016/j.renene.2025.123445
- Leveraging Quantum Annealing for Layout Optimization L. Nigro et al. 10.1002/qute.202500358
2 citations as recorded by crossref.
Latest update: 27 Oct 2025
Short summary
The use of wind energy has been growing over the last few decades, and further increase is predicted. As the wind energy industry is starting to consider larger wind farms, the existing numerical methods for analysis of small and medium wind farms need to be improved. In this article, we have explored different strategies to tackle the problem in a feasible and timely way. The final product is a set of recommendations when carrying out trade-off analysis on large wind farms.
The use of wind energy has been growing over the last few decades, and further increase is...
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