1. 河海大学 新能源学院,常州,213200
2. 内蒙古工业大学 风能太阳能利用技术教育部重点实验室,呼和浩特,010051
李文锋,研究方向:漂浮式风力机多自由度运动尾流特性研究. E-mail:liwenfeng901@163.com
赵振宙*,研究方向:风力机空气动力学. E-mail:joephy@163.com
纸质出版:2026
移动端阅览
李文锋, 赵振宙, 魏赏赏, 等. 纵荡运动下漂浮式风力机尾流模型[J]. 空气动力学学报, 2026, 44(6): 133−145.
Li Wenfeng, Zhao Zhenzhou, Wei Shangshang, et al. Wake model of a floating offshore wind turbine under surge motion[J]. 2026, 44(6): 133-145.
李文锋, 赵振宙, 魏赏赏, 等. 纵荡运动下漂浮式风力机尾流模型[J]. 空气动力学学报, 2026, 44(6): 133−145. DOI: 10.7638/kqdlxxb-2025.0163
Li Wenfeng, Zhao Zhenzhou, Wei Shangshang, et al. Wake model of a floating offshore wind turbine under surge motion[J]. 2026, 44(6): 133-145. DOI: 10.7638/kqdlxxb-2025.0163.
纵荡运动会显著影响漂浮式风力机( floating offshore wind turbine
FOWT)的推力系数变化和尾流发展特性。本文在高阶高斯模型的基础上,考虑FOWT纵荡运动引起的附加风速,提出了FOWT尾流模型HG-DFOWT(high-order Gaussian dynamic floating offshore wind turbine model),以预测风力机尾流分布及推力系数变化。模型首先修正了FOWT纵荡时轮毂位置变化,然后通过纵荡产生的附加速度修正风轮处相对入流风速,其次根据FOWT一阶正弦运动建立推力系数动态变化模型,最后将模型预测结果与风洞试验结果和CFD数值模拟结果进行对比,验证模型的可靠性。结果表明,逆风运动下,模型对FOWT的垂向尾流预测结果与风洞试验结果的均方根误差为4.04%,顺风运动下,误差为1.47%。修正后的推力系数与CFD计算结果具有良好的一致性,高频纵荡下(
f
≥ 0.072 Hz),两者的平均相对误差小于1%。此外,还分析了一个纵荡周期内不同时刻的尾流分布特性,结果发现,FOWT下游相同位置处尾流亏损在时均值附近呈周期性波动,尾流中心风速受纵荡频率影响较大,高频运动下(
f
= 0.09 Hz)波动幅值达7.1%。本文模型可为构建漂浮式风电场布局优化模型提供参考。
Surge motion significantly affects the thrust coefficient variation and wake development characteristics of floating offshore wind turbines (FOWTs). Based on the high-order Gaussian model
this paper proposes a FOWT wake model
designated as HG-DFOWT (high-order Gaussian dynamic floating offshore wind turbine model)
which incorporates the additional wind speed induced by FOWT surge motion
to predict the wake distribution and
thrust coefficient variation of the wind turbine. The model first corrects the variation in hub position during FOWT surge. Then
it modifies the relative inflow velocity at the rotor plane using the additional velocity induced by surge. Subsequently
a dynamic thrust coefficient model is established based on the first-order sinusoidal surge motion of the FOWT. Finally
the model predictions are compared with wind tunnel experimental results and CFD numerical simulation results to validate the reliability of the model. The results indicate that
under upwind motion
the root mean square error between the model's predicted vertical wake profiles and the wind tunnel experimental results is 4.04%
while under downwind motion
the error is 1.47%. The corrected thrust coefficient shows good consistency with the CFD calculation results
with an average relative error of less than 1% under high-frequency surge conditions (
f
≥ 0.072 Hz). In addition
the wake distribution characteristics at different time within a surge cycle are analyzed. It is found that the wake deficit at the same downstream position of the FOWT exhibits periodic fluctuations around the time-averaged value
and the wake center velocity is significantly influenced by the surge frequency
with a fluctuation amplitude reaching 7.1% under high-frequency motion (
f
= 0.09 Hz). The proposed model provides a reference for layout optimization of floating wind farms.
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