Wind farm layout optimization in complex terrain considering wind turbine fatigue load constraint

Currently, mountainous wind farm layout optimization generally does not take fatigue loads into account. However, due to the complexity of the mountainous flow characteristics, layout optimization focusing solely on power generation may lead to excessive fatigue loads on certain turbines, which could affect the long-term profitability of the entire wind farm. To address this issue, this study proposes a wind farm layout optimization approach for complex terrain considering wind turbine fatigue load constraint. This approach consists of three basic parts, i.e., computational fluid dynamics, complex-terrain wake model, and fatigue load surrogate model. These basic parts are used to obtain a wind resource map for complex terrain, calculate wake effects, and rapidly predict fatigue loads of wind turbines, respectively. After that, an optimization framework in complex terrain is presented in which the objective function and load constraint are involved. The core of the optimization framework is that only solutions that satisfy the fatigue load constraint will be further optimized. Finally, a case study was utilized to validate the effectiveness of the proposed approach. The results showed that neglecting load constraint in the layout optimization of wind farm in complex terrain can lead to significant load increases of some wind turbines. By incorporating a reasonable load constraint, a substantial increase in power generation can be achieved while controlling turbine loads within acceptable ranges. However, this approach may sacrifice power generation if the constraints are prescribed to be too strict.

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Institutions

Publication Details

Journal
Physics of Fluids
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0249777
Citations
3
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
14.98

Funders

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article

Wind farm layout optimization in complex terrain considering wind turbine fatigue load constraint

Yan Jiang, Liuliu Peng, Qingshan Yang, Binbin Wang et al.
3 citations
Physics of Fluids
Wind Energy Research and Development
14.98
article

Wind farm layout optimization in complex terrain considering wind turbine fatigue load constraint

Yan Jiang, Liuliu Peng, Qingshan Yang, Binbin Wang, Weijie Liu, Guoqing Huang
article en
3 citations

Abstract

Currently, mountainous wind farm layout optimization generally does not take fatigue loads into account. However, due to the complexity of the mountainous flow characteristics, layout optimization focusing solely on power generation may lead to excessive fatigue loads on certain turbines, which could affect the long-term profitability of the entire wind farm. To address this issue, this study proposes a wind farm layout optimization approach for complex terrain considering wind turbine fatigue load constraint. This approach consists of three basic parts, i.e., computational fluid dynamics, complex-terrain wake model, and fatigue load surrogate model. These basic parts are used to obtain a wind resource map for complex terrain, calculate wake effects, and rapidly predict fatigue loads of wind turbines, respectively. After that, an optimization framework in complex terrain is presented in which the objective function and load constraint are involved. The core of the optimization framework is that only solutions that satisfy the fatigue load constraint will be further optimized. Finally, a case study was utilized to validate the effectiveness of the proposed approach. The results showed that neglecting load constraint in the layout optimization of wind farm in complex terrain can lead to significant load increases of some wind turbines. By incorporating a reasonable load constraint, a substantial increase in power generation can be achieved while controlling turbine loads within acceptable ranges. However, this approach may sacrifice power generation if the constraints are prescribed to be too strict.

Physics of FluidsVol. 37(2)
Southwest University (CN), Chongqing University (CN), China Power Engineering Consulting Group (China) (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Higher Education Discipline Innovation Project
Openalex Percentile: Top 2%
Wind Energy Research and Development
14.98
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