Impact of incoming turbulence intensity and turbine spacing on output power density: A study with two 5MW offshore wind turbines

被引:5
作者
Liu, Songyue [1 ]
Li, Qiusheng [1 ]
Lu, Bin [1 ]
He, Junyi [1 ]
机构
[1] City Univ Hong Kong, Dept Architecture & Civil Engn, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Offshore wind turbine; Output power density; Incoming turbulence intensity; Turbine spacing; LES-ALM method; Active learning; LARGE-EDDY SIMULATION; INFLOW; TUNNEL; FARM;
D O I
10.1016/j.apenergy.2024.123648
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Turbulence intensity in offshore environments has significant effects on the performance of offshore wind turbines. To maximize output power of offshore wind turbines within a limited space, i.e., achieving maximum output power density, it is essential to investigate the influences of incoming turbulence intensity and turbine spacing on output power density. The Large Eddy Simulation coupled Actuator Line Method (LES-ALM) is used in this study to simulate two utility-scale NREL-5 MW wind turbines in different turbulent environments and turbine spacings. The optimal incoming turbulence intensity and turbine spacing are identified using an active learning method. The determined optimal parameters act as a benchmark for the impact analysis. The findings indicate that the increase of turbine spacing initially results in a considerable rise in the output power density of the two NREL-5 MW wind turbines, followed by a slight downward trend across various turbulent environments. The increase of the incoming turbulence leads to a steady rise of the output power density when the turbine spacing is less than 5.1 D ( D is the rotor diameter), while a rise followed by a decrease in the output power density is observed for the turbine spacing exceeding 5.1 D . Notably, when the turbine spacing is 5.9 D and the reference value of turbulence intensity is 15.2%, the output power density reaches its global maximum.
引用
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页数:14
相关论文
共 39 条
[11]   The influence of incoming turbulence on the dynamic modes of an NREL-5MW wind turbine wake [J].
De Cillis, Giovanni ;
Cherubini, Stefania ;
Semeraro, Onofrio ;
Leonardi, Stefano ;
De Palma, Pietro .
RENEWABLE ENERGY, 2022, 183 :601-616
[12]   A simple analytical wind park model considering atmospheric stability [J].
Emeis, S. .
WIND ENERGY, 2010, 13 (05) :459-469
[13]   Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain [J].
Han, Xingxing ;
Liu, Deyou ;
Xu, Chang ;
Shen, Wen Zhong .
RENEWABLE ENERGY, 2018, 126 :640-651
[14]   Wind turbine power curves incorporating turbulence intensity [J].
Hedevang, Emil .
WIND ENERGY, 2014, 17 (02) :173-195
[15]   A general inflow turbulence generator for large eddy simulation [J].
Huang, S. H. ;
Li, Q. S. ;
Wu, J. R. .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2010, 98 (10-11) :600-617
[16]  
Jo Jun-Mo, 2019, [The Journal of The Korea Institute of Electronic Communication Sciences, 한국전자통신학회 논문지], V14, P547
[17]  
Jonkman J., 2009, NREL/TP-500-38060, DOI [10.1002/ajmg.10175, DOI 10.2172/947422]
[18]   Optimization of a wind farm by coupled actuator disk and mesoscale models to mitigate neighboring wind farm wake interference from repowering perspective [J].
Khan, Mehtab Ahmad ;
Javed, Adeel ;
Shakir, Sehar ;
Syed, Abdul Haseeb .
APPLIED ENERGY, 2021, 298
[19]  
Konyushkova K, 2017, ADV NEUR IN, V30
[20]   Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (Part I: Power performance) [J].
Li, Qing'an ;
Murata, Junsuke ;
Endo, Masayuki ;
Maeda, Takao ;
Kamada, Yasunari .
ENERGY, 2016, 113 :713-722