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Multi-objective layout optimization for wind farms based on non-uniformly distributed turbulence and a new three-dimensional multiple wake model.

Authors :
Ling, Ziyan
Zhao, Zhenzhou
Liu, Yige
Liu, Huiwen
Ali, Kashif
Liu, Yan
Wen, Yifan
Wang, Dingding
Li, Shijun
Su, Chunhao
Source :
Renewable Energy: An International Journal. Jun2024, Vol. 227, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Wind farm layout optimization (WFLO) can reduce the turbulence intensity on the wind turbines while maximizing power generation. To accurately compute turbulence intensity distribution in the wind farm, we utilize the innovative three-dimensional cosine-shaped turbulence intensity (3D-COTI) model. By integrating the three-dimensional cosine-shaped linear entrainment (3DCLE) wake model previously developed by the authors, we introduce a new multiple wind turbine wake model (3DCLE-M). This model considers the wake superposition effect, enabling precise calculation of power generation. Building upon the 3D-COTI and 3DCLE-M models, we propose a multi-objective WFLO approach to maximize power generation and minimize streamwise turbulence intensity in the wind-turbine-swept area. The results indicate that under maximized power generation, this approach significantly reduces turbulence intensity and its non-uniform distribution in the wind-turbine-swept area. In two ideal cases, the maximum turbulence intensity in all wind-turbine-swept areas of the optimized layout is 25 % and 3.8 % lower than that of the selected benchmark layout. By optimizing the layout of the Horns Rev offshore wind farm, a new layout can be obtained with increased total power output by 1.58 % and the reduced total duration of high-fatigue-load wind turbines under high turbulence intensity by 25 % compared to the benchmark. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09601481
Volume :
227
Database :
Academic Search Index
Journal :
Renewable Energy: An International Journal
Publication Type :
Academic Journal
Accession number :
177223643
Full Text :
https://doi.org/10.1016/j.renene.2024.120558