摘要
在大型风电场中,机组间尾流效应会增加下游机组疲劳载荷,对机组运行安全造成不良影响。通过大涡模拟,在给定风况下开展测试,获取1台风电机组的动态尾流。利用数据驱动的动态模态分解方法,构建动态尾流的线性降维模型,通过2种定量化指标,验证了这种线性降维近似方法的有效性,并探索了模型阶次与模型适配度的相关性。在此基础上,通过对主要动态模态的频域特性分析和可视化分解,明确了风电机组动态尾流的主要低阻尼模态。结合傅里叶变换方法,研究了尾流区域中近尾流区与远尾流区的频域特性差异。研究结果表明,动态模态分解作为兼具系统辨识与频域分析的方法在风电机组动态尾流的建模中可以取得较高的建模精度,在时域与频域角度均有较好的适应度。
The fatigue load due to wind turbine wake takes an adverse effect on safe operation in large wind farms. The wind turbine is simulated by using large-eddy simulation method under a given wind condition,dynamic wake is obtained. Using a data-driven dynamic mode decomposition method,a linear reduced-order model is obtained to model the dynamic wake. The reduced-order model is validated with two quantitative indexes for its effectiveness,and the relations between the system order and the fitness is studied.Based on this work,dominant modes with lower damping ratio of the wind turbine wake is analyzed by frequency domain analysis and visualization decomposition. Furtherly,the difference in frequency domain of the near-wake zone and far-wake zone is analyzed by using Fourier transform. Results indicate that the dynamic mode decomposition suits well both identification and frequency domain analysis method. Good modeling accuracy in both time and frequency domains can be guaranteed.
作者
陈振宇
刘吉臻
林忠伟
谢镇
李庚达
李雄威
胡峰
CHEN Zhenyu;LIU Jizhen;LIN Zhongwei;XIE Zhen;LI Gengda;LI Xiongwei;HU Feng(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China;Guodian New Energy Technology Research Institute Co.Ltd.,Beijing 102209,China;CHN ENERGY(Shandong)New Energy Co.,Ltd,Jinan 250099,China)
出处
《智慧电力》
北大核心
2020年第7期1-7,37,共8页
Smart Power
基金
国家自然科学基金资助项目(U1766204,61973114)
国家能源集团科技项目(GJNY-19-87)。
关键词
风电机组
尾流效应
动态模态分解
频域分析
wind turbine
wake effect
dynamic mode decomposition
frequency domain analysis
