Articles | Volume 8, issue 5
https://doi.org/10.5194/wes-8-865-2023
© Author(s) 2023. 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-8-865-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jun 2023
Research article |
| 01 Jun 2023
| 01 Jun 2023
A comparison of eight optimization methods applied to a wind farm layout optimization problem
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
National Renewable Energy Laboratory, Golden, CO 80401, USA
Nicholas F. Baker
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Paul Malisani
Applied Mathematics Department, IFP Energies nouvelles, 1 et 4 avenue de Bois-Préau, 92852 Rueil-Malmaison, France
Erik Quaeghebeur
Uncertainty in AI Group, Eindhoven University of Technology, 5612 AZ Eindhoven, the Netherlands
Sebastian Sanchez Perez-Moreno
RWE Renewables GmbH, 20354 Hamburg, Germany
John Jasa
National Renewable Energy Laboratory, Golden, CO 80401, USA
Christopher Bay
National Renewable Energy Laboratory, Golden, CO 80401, USA
Federico Tilli
TU Delft, 2628 CD Delft, Netherlands
David Bieniek
RWE Renewables GmbH, 20354 Hamburg, Germany
Nick Robinson
UL Renewables, British Columbia, Kelowna, Canada
Andrew P. J. Stanley
National Renewable Energy Laboratory, Golden, CO 80401, USA
Wesley Holt
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Andrew Ning
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
National Renewable Energy Laboratory, Golden, CO 80401, USA
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Cited
11 citations as recorded by crossref.
- Evaluating the potential of a wake steering co-design for wind farm layout optimization through a tailored genetic algorithm M. Baricchio et al. 10.5194/wes-9-2113-2024
- A neighborhood search integer programming approach for wind farm layout optimization J. Pérez-Rúa et al. 10.5194/wes-8-1453-2023
- 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
- Wake Mixing Control For Floating Wind Farms: Analysis of the Implementation of the Helix Wake Mixing Strategy on the IEA 15-MW Floating Wind Turbine D. van den Berg et al. 10.1109/MCS.2024.3432341
- Robust wind farm layout optimization M. Sinner & P. Fleming 10.1088/1742-6596/2767/3/032036
- Need For Speed: Fast Wind Farm Optimization M. Sarcos et al. 10.1088/1742-6596/2767/9/092088
- A Two-Step Grid–Coordinate Optimization Method for a Wind Farm with a Regular Layout Using a Genetic Algorithm G. Huang et al. 10.3390/en17133273
- FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization M. LoCascio et al. 10.1002/we.2954
- An optimization framework for wind farm layout design using CFD-based Kriging model Z. Wang et al. 10.1016/j.oceaneng.2023.116644
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
- Wind farm layout optimization approach using bio-inspired meta-heuristic algorithm to minimize wake effect S. Pranupa et al. 10.1007/s40435-023-01172-y
10 citations as recorded by crossref.
- Evaluating the potential of a wake steering co-design for wind farm layout optimization through a tailored genetic algorithm M. Baricchio et al. 10.5194/wes-9-2113-2024
- A neighborhood search integer programming approach for wind farm layout optimization J. Pérez-Rúa et al. 10.5194/wes-8-1453-2023
- 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
- Wake Mixing Control For Floating Wind Farms: Analysis of the Implementation of the Helix Wake Mixing Strategy on the IEA 15-MW Floating Wind Turbine D. van den Berg et al. 10.1109/MCS.2024.3432341
- Robust wind farm layout optimization M. Sinner & P. Fleming 10.1088/1742-6596/2767/3/032036
- Need For Speed: Fast Wind Farm Optimization M. Sarcos et al. 10.1088/1742-6596/2767/9/092088
- A Two-Step Grid–Coordinate Optimization Method for a Wind Farm with a Regular Layout Using a Genetic Algorithm G. Huang et al. 10.3390/en17133273
- FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization M. LoCascio et al. 10.1002/we.2954
- An optimization framework for wind farm layout design using CFD-based Kriging model Z. Wang et al. 10.1016/j.oceaneng.2023.116644
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
Latest update: 13 Dec 2024
Short summary
This work compares eight optimization algorithms (including gradient-based, gradient-free, and hybrid) on a wind farm optimization problem with 4 discrete regions, concave boundaries, and 81 wind turbines. Algorithms were each run by researchers experienced with that algorithm. Optimized layouts were unique but with similar annual energy production. Common characteristics included tightly-spaced turbines on the outer perimeter and turbines loosely spaced and roughly on a grid in the interior.
This work compares eight optimization algorithms (including gradient-based, gradient-free, and...
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