A numerical simulation framework for wakes downstream of large wind farms based on equivalent roughness model

被引:0
|
作者
Jia, Rui [1 ]
Ge, Mingwei [1 ]
Zhang, Ziliang [2 ]
Li, Xintao [1 ]
Du, Bowen [1 ]
机构
[1] North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewable, Beijing 102206, Peoples R China
[2] China Three Gorges Corp, Sci & Technol Res Inst, Beijing 101199, Peoples R China
基金
中国国家自然科学基金;
关键词
Large-scale wind farm; Wind-farm wakes; Equivalent roughness model; OpenFOAM; SUBGRID-SCALE MODEL; ACTUATOR DISK; ENERGY; PARAMETERIZATION; SENSITIVITY; TURBULENCE; IMPACTS; SURFACE; CHINA; POWER;
D O I
10.1016/j.energy.2024.132600
中图分类号
O414.1 [热力学];
学科分类号
摘要
Accurate assessment of the wake effect of wind farm clusters is of great significance for the development of wind power bases, yet there is currently a deficiency in numerical simulation methods with high accuracy and simple modeling. To address this issue, a numerical simulation framework for large wind-farm wakes based on a wind farm parameterization model is proposed, and is then implemented based on the open-source CFD software OpenFOAM. In this framework, a newly proposed wind farm equivalent roughness model is adopted to parameterize wind farms and incorporated into the simulation via the wall stress model. To validate the method, the large-eddy simulation based on the actuator disk model resolving all the turbines in the wind farm is taken as a benchmark. Thirty two cases including spanwise infinite wind farms and finite wind farms with different streamwise turbine spacings, spanwise turbine spacings, wind turbine thrust coefficients, and roughness lengths of ground surface are set to analyze the sensitivity of the framework to different wind farm parameters. Results show that the proposed method predicts the velocity deficit and turbulence intensity downstream of the wind farm accurately. Compared to the classical wake superposition model, the prediction accuracy of the velocity deficit is improved by more than 30 %. Furthermore, without resolving the turbines using fine mesh, the framework shows a high potential to reduce computational costs compared with the turbine-resolved simulation.
引用
收藏
页数:15
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