An improved dynamic model for wind-turbine wake flow

被引:6
作者
Feng, Dachuan [1 ,2 ,3 ]
Gupta, Vikrant [2 ,3 ]
Li, Larry K. B. [1 ,4 ]
Wan, Minping [2 ,3 ,5 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Mech & Aerosp Engn, Clear Water Bay, Hong Kong, Peoples R China
[2] Southern Univ Sci & Technol, Dept Mech & Aerosp Engn, Guangdong Prov Key Lab Turbulence Res & Applicat, Shenzhen 518055, Peoples R China
[3] Southern Univ Sci & Technol, Guangdong Hong Kong Macao Joint Lab Data Driven Fl, Hong Kong 518055, Guangdong, Peoples R China
[4] Hong Kong Univ Sci & Technol, Guangdong Hong Kong Macao Joint Lab Data Driven Fl, Clear Water Bay, Hong Kong, Guangdong, Peoples R China
[5] Southern Univ Sci & Technol, Jiaxing Res Inst, Jiaxing 314031, Peoples R China
基金
中国国家自然科学基金;
关键词
Wake dynamics; Wake modeling; Wind energy; Wind turbine; VALIDATION; STABILITY;
D O I
10.1016/j.energy.2023.130167
中图分类号
O414.1 [热力学];
学科分类号
摘要
We present an improved dynamic model to predict the time-varying characteristics of the far-wake flow behind a wind turbine. Our model, based on the FAST.Farm engineering model, is novel in that it estimates the turbulence generated by convective instabilities, which selectively amplifies the inflow velocity fluctuations. Our model also incorporates scale dependence when calculating the wake meandering induced by the passive wake meandering mechanism. For validation, our model is compared with FAST.Farm and largeeddy simulation (LES). For the mean flow, our model agrees well with LES in terms of the wake deficit and wake width, but the FAST.Farm model underestimates the former and overestimates the latter. For the instantaneous flow, our model predicts well the wake-center deflection and turbulent kinetic energy, reducing the discrepancies in the spectral characteristics by more than a factor of two relative to LES, depending on the Strouhal number. By incorporating two key mechanisms governing the far-wake dynamics, our model can predict more accurately the dynamic wake evolution, making it suitable for real -time calculations of wind farm performance.
引用
收藏
页数:6
相关论文
共 46 条
[21]   A pragmatic approach to wind farm simulations using the dynamic wake meandering model [J].
Keck, Rolf-Erik ;
Undheim, Ove .
WIND ENERGY, 2015, 18 (09) :1671-1682
[22]   Two improvements to the dynamic wake meandering model: including the effects of atmospheric shear on wake turbulence and incorporating turbulence build-up in a row of wind turbines [J].
Keck, Rolf-Erik ;
de Mare, Martin ;
Churchfield, Matthew J. ;
Lee, Sang ;
Larsen, Gunner ;
Madsen, Helge Aagaard .
WIND ENERGY, 2015, 18 (01) :111-132
[23]   On atmospheric stability in the dynamic wake meandering model [J].
Keck, Rolf-Erik ;
de Mare, Martin ;
Churchfield, Matthew J. ;
Lee, Sang ;
Larsen, Gunner ;
Aagaard Madsen, Helge .
WIND ENERGY, 2014, 17 (11) :1689-1710
[24]   Implementation of a Mixing Length Turbulence Formulation Into the Dynamic Wake Meandering Model [J].
Keck, Rolf-Erik ;
Veldkamp, Dick ;
Madsen, Helge Aagaard ;
Larsen, Gunner .
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2012, 134 (02)
[25]  
Kirby A, 2023, Arxiv, DOI arXiv:2301.01699
[26]   FAST.Farm load validation for single wake situations at alpha ventus [J].
Kretschmer, Matthias ;
Jonkman, Jason ;
Pettas, Vasilis ;
Cheng, Po Wen .
WIND ENERGY SCIENCE, 2021, 6 (05) :1247-1262
[27]   Wake meandering: A pragmatic approach [J].
Larsen, Gunner C. ;
Madsen, Helge Aa. ;
Thomsen, Kenneth ;
Larsen, Torben J. .
WIND ENERGY, 2008, 11 (04) :377-395
[28]   Calibration and Validation of the Dynamic Wake Meandering Model for Implementation in an Aeroelastic Code [J].
Madsen, H. Aa. ;
Larsen, G. C. ;
Larsen, T. J. ;
Troldborg, N. ;
Mikkelsen, R. .
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2010, 132 (04)
[29]   Far-wake meandering induced by atmospheric eddies in flow past a wind turbine [J].
Mao, X. ;
Sorensen, J. N. .
JOURNAL OF FLUID MECHANICS, 2018, 846 :190-209
[30]   Toward Development of a Stochastic Wake Model: Validation Using LES and Turbine Loads [J].
Moon, Jae Sang ;
Manuel, Lance ;
Churchfield, Matthew J. ;
Lee, Sang ;
Veers, Paul S. .
ENERGIES, 2018, 11 (01)