基于CFD仿真的漂浮式风力机尾流模型研究

胡伟成; 刘震卿

doi:10.7638/kqdlxxb-2025.0133

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基于CFD仿真的漂浮式风力机尾流模型研究

研究专栏——新一代风电空气动力学 | 更新时间：2026-07-11

- 基于CFD仿真的漂浮式风力机尾流模型研究
- A study on the wake model for floating offshore wind turbines based on CFD simulation
- 空气动力学学报 2026年44卷第6期页码：113-122
- 作者机构：
  
  1. 华东交通大学山区土木工程安全与韧性全国重点实验室,南昌,330013
  2. 华中科技大学土木与水利工程学院,武汉,430074
- 作者简介：
  
  胡伟成，研究方向：风工程与风能利用. E-mail：huweicheng92@163.com
  刘震卿*，研究方向：风工程与风能利用. E-mail：liuzhenqing@hust.edu.cn
- 基金信息：
  
  国家自然科学基金（52478516，52208479）;江西省自然科学基金（20232BAB204082）;赣鄱俊才支持计划（20243BCE51162）
- DOI：10.7638/kqdlxxb-2025.0133
  中图分类号： TM614
- 纸质出版：2026
- 稿件说明：
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胡伟成, 刘震卿. 基于CFD仿真的漂浮式风力机尾流模型研究[J]. 空气动力学学报, 2026, 44(6): 113−122.

Hu Weicheng, Liu Zhenqing. A study on the wake model for floating offshore wind turbines based on CFD simulation[J]. 2026, 44(6): 113-122.
胡伟成, 刘震卿. 基于CFD仿真的漂浮式风力机尾流模型研究[J]. 空气动力学学报, 2026, 44(6): 113−122. DOI： 10.7638/kqdlxxb-2025.0133

Hu Weicheng, Liu Zhenqing. A study on the wake model for floating offshore wind turbines based on CFD simulation[J]. 2026, 44(6): 113-122. DOI： 10.7638/kqdlxxb-2025.0133.

摘要

针对漂浮式风力机复杂运动导致的尾流预测难题，本文建立了基于改进致动盘模型的高精度CFD数值仿真模型。该模型采用Realizable

湍流模型，并开发了可精准模拟多运动状态下体积力的UDF（user-defined function）程序。将本文方法与其他4种湍流模型进行了系统对比，并通过风洞试验结果进行验证，结果表明，基于改进致动盘模型的Realizable

模型可精准捕捉风力机尾流速度和湍流强度分布。基于对80种单一运动工况的Sobol敏感性分析表明：来流湍流与推力系数对尾流的影响显著大于运动参数，运动周期的影响基本可忽略，纵摇、纵荡及横摇为主导运动形式。据此，本文提出一种Jensen-Gaussian尾流解析模型，在传统高斯分布框架中引入运动幅值参数，其在单一运动下平均预测误差仅为2.0%，较传统Jensen与BPA尾流模型降低了3.8%～6.6%。针对耦合运动工况，对比5种尾流叠加模型，发现最大亏损叠加模型（maximum loss

ML）对耦合运动尾流预测的精度最高，平均误差仅为1.9%，实现了多运动协同作用下的高效精准预测。本研究为深远海风电场布局优化与运行控制提供了高精度、低成本的尾流预测工具链。

Abstract

To address the challenge of wake prediction caused by complex motions of floating offshore wind turbines

this paper presents a high-precision CFD numerical model based on an improved actuator disk model. A UDF (user-defined function) program is developed to accurately compute body forces under multiple motion states. The proposed method

together with four other turbulence models

is systematically compared against

wind tunnel measurements. The simulation results are validated against wind tunnel tests. The Realizable

model with the improved actuator disk model accurately captures the velocity and turbulence intensity distributions in the turbine wake. A Sobol sensitivity analysis is conducted on 80 single-motion cases. Results show that inflow turbulence and thrust coefficient dominate the wake characteristics. Their influence is significantly greater than that of motion parameters. The motion period has a negligible effect. Pitch

surge

and roll are identified as the dominant motion forms. A Jensen-Gaussian wake model is then proposed. This model introduces motion amplitude parameters into the traditional Gaussian distribution framework. For single-motion cases

the average prediction error is only 2.0%. This error is 3.8% to 6.6% lower than that of the conventional Jensen and BPA models. For coupled motion cases

five wake superposition models are compared. The maximum loss (ML) model achieves the highest prediction accuracy. Its average error is only 1.9%. This approach enables efficient and accurate wake simulation under multi-motion synergistic effects. This study provides a high-precision

low-cost wake prediction toolchain for the layout optimization and operational control of deep-sea offshore wind farms.

关键词

Keywords

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