Articles | Volume 6, issue 5
https://doi.org/10.5194/wes-6-1143-2021
© Author(s) 2021. 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-6-1143-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Sep 2021
Research article |
| 09 Sep 2021
| 09 Sep 2021
Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant
National Renewable Energy Laboratory, National Wind Technology Center, Boulder, CO 80303, USA
Owen Roberts
National Renewable Energy Laboratory, National Wind Technology Center, Boulder, CO 80303, USA
Jennifer King
National Renewable Energy Laboratory, National Wind Technology Center, Boulder, CO 80303, USA
Christopher J. Bay
National Renewable Energy Laboratory, National Wind Technology Center, Boulder, CO 80303, USA
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Cited
16 citations as recorded by crossref.
- FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models M. LoCascio et al. 10.5194/wes-7-1137-2022
- Stochastic gradient descent for wind farm optimization J. Quick et al. 10.5194/wes-8-1235-2023
- Simultaneous sizing and energy management of multi-energy Virtual Power Plants operating in regulated energy markets A. Elgamal et al. 10.1016/j.ijepes.2024.110171
- Multi-Timescale Wind-Based Hybrid Energy Systems A. Stanley et al. 10.1088/1742-6596/2265/4/042062
- Automatic grouping of wind turbine types via multi-objective formulation for nonuniform wind farm layout optimization using an analytical wake model A. de Moura Ribeiro et al. 10.1016/j.enconman.2024.118759
- Topology optimization of wind farm layouts N. Pollini 10.1016/j.renene.2022.06.019
- Offshore wind farm layout optimization using ensemble methods K. Eikrem et al. 10.1016/j.renene.2023.119061
- Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant A. Stanley & J. King 10.1016/j.apenergy.2022.119139
- GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization Y. Li et al. 10.32604/ee.2023.045228
- Assessing and comparing a DDPG model and GA optimization for a heat and power virtual power plant operating in a power purchase agreement scheme A. Elgamal et al. 10.1016/j.heliyon.2024.e24318
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
- Offshore wind farm layout optimization accounting for participation in secondary reserve markets T. Nguyen et al. 10.5194/wes-10-1661-2025
- Optimization Method of Wind Turbine Locations in Complex Terrain Areas Using a Combination of Simulation and Analytical Models D. Thin et al. 10.1109/ACCESS.2025.3584560
- 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
- Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm N. Kirchner-Bossi & F. Porté-Agel 10.1016/j.renene.2023.119524
- Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients M. LoCascio et al. 10.1063/5.0237778
16 citations as recorded by crossref.
- FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models M. LoCascio et al. 10.5194/wes-7-1137-2022
- Stochastic gradient descent for wind farm optimization J. Quick et al. 10.5194/wes-8-1235-2023
- Simultaneous sizing and energy management of multi-energy Virtual Power Plants operating in regulated energy markets A. Elgamal et al. 10.1016/j.ijepes.2024.110171
- Multi-Timescale Wind-Based Hybrid Energy Systems A. Stanley et al. 10.1088/1742-6596/2265/4/042062
- Automatic grouping of wind turbine types via multi-objective formulation for nonuniform wind farm layout optimization using an analytical wake model A. de Moura Ribeiro et al. 10.1016/j.enconman.2024.118759
- Topology optimization of wind farm layouts N. Pollini 10.1016/j.renene.2022.06.019
- Offshore wind farm layout optimization using ensemble methods K. Eikrem et al. 10.1016/j.renene.2023.119061
- Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant A. Stanley & J. King 10.1016/j.apenergy.2022.119139
- GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization Y. Li et al. 10.32604/ee.2023.045228
- Assessing and comparing a DDPG model and GA optimization for a heat and power virtual power plant operating in a power purchase agreement scheme A. Elgamal et al. 10.1016/j.heliyon.2024.e24318
- Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations M. Hall et al. 10.1088/1742-6596/2767/6/062038
- Offshore wind farm layout optimization accounting for participation in secondary reserve markets T. Nguyen et al. 10.5194/wes-10-1661-2025
- Optimization Method of Wind Turbine Locations in Complex Terrain Areas Using a Combination of Simulation and Analytical Models D. Thin et al. 10.1109/ACCESS.2025.3584560
- 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
- Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm N. Kirchner-Bossi & F. Porté-Agel 10.1016/j.renene.2023.119524
- Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients M. LoCascio et al. 10.1063/5.0237778
Latest update: 28 Aug 2025
Short summary
Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15 to 54 for the cases in this paper, depending on the metric that is optimized.
Wind farm layout optimization is an essential part of wind farm design. In this paper, we...
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