Research and Verification of Three-dimensional Wake Velocity Model for Wind Turbine Based on High-order Gaussian Function

被引：0

作者：

Wei, Hong ^{[1
]}

Zhao, Zhenzhou ^{[1
]}

Liu, Yige ^{[1
]}

Wei, Shangshang ^{[1
]}

Liu, Huiwen ^{[1
]}

Liu, Yan ^{[1
]}

Luo, Qiao ^{[2
]}

机构：

[1] School of Electrical and Power Engineering, Hohai University, Jiangsu Province, Nanjing

[2] Jiangsu Wind Power Engineering Technology Center, Nanjing Vocational University of Industry Technology, Jiangsu Province, Nanjing

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2025年 / 45卷 / 13期

基金：

中国国家自然科学基金;

关键词：

high-order Gaussian function; wake model; wake velocity; wind turbine;

D O I：

10.13334/j.0258-8013.pcsee.240116

中图分类号：

学科分类号：

摘要：

Under natural conditions, the wake velocity distribution approximates top-hat shape in the near wake center, and approximates Gaussian shape in the far wake .To improve the prediction accuracy of the wake distribution, a three-dimensional high-order Gaussian Laminar Elongated wake model is established by modifying the wake velocity distribution with high-order Gaussian function. Field tests and wind tunnel tests show that the proposed model can effectively describe the radial and vertical spatial distribution of wake flow. Under different wind speeds, the maximum radial relative error is 7.29% and the minimum is 1.4%; the maximum vertical relative error is 7.64% and the minimum is 3.87%, which means the proposed model can well predict velocity distribution in the whole wake region. © 2025 Chinese Society for Electrical Engineering. All rights reserved.

引用

页码：5099 / 5105

页数：6

共 20 条

[1]

WEI Shangshang, XU Chang, YAN Jie, Et al., Wake control of wind farm based on model predictive control considering propagation delay, Proceedings of the CSEE, 44, 5, pp. 1813-1822, (2024)

[2]

ZHENG Yidan, LIU Huiwen, ZHENG Yuan, Et al., Experimental study on the wakes evolution of a staggered wind farm, Proceedings of the CSEE, 43, 4, pp. 1463-1470, (2023)

[3]

Xiaoxia GAO, Bingbing LI, WANG Tengyuan, Et al., Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements [J], Applied Energy, 260, (2020)

[4]

LING Ziyan, ZHAO Zhenzhou, LIU Yige, Et al., Study and validation of three-dimensional entrainment wake model for wind-turbine, Proceedings of the CSEE, 43, 17, (2023)

[5]

WANG J, FOLEY S, NANOS E M, Et al., Numerical and experimental study of wake redirection techniques in a boundary layer wind tunnel[J], Journal of Physics: Conference Series, 854, (2017)

[6]

SCHREIBER J, BALBAA A, BOTTASSO C L., Brief communication:a double-Gaussian wake model[J], Wind Energy Science, 5, 1, pp. 237-244, (2020)

[7]

DOUBRAWA P, DEBNATH M, MORIARTY P J, Et al., Benchmarks for model validation based on LiDAR wake measurements[J], Journal of Physics:Conference Series, 1256, 1, (2019)

[8]

SUMNER J, ESPANA G, MASSON C, Et al., Evaluation of RANS/actuator disk modelling of wind turbine wake flow using wind tunnel measurements, International Journal of Engineering Systems Modelling and Simulation, 5, 1-3, pp. 147-158, (2013)

[9]

LI Qing'an, MURATA J, ENDO M, Et al., Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine(part II:wake characteristics)[J], Energy, 113, pp. 1304-1315, (2016)

[10]

LIU Yige, ZHAO Zhenzhou, MA Yuanzhuo, Et al., Active wake control strategy of tandem wind turbines based on whale optimization algorithm, Proceedings of the CSEE, 44, 9, pp. 3702-3709, (2024)

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