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作 者:王雅娴 赵峰[1,2] WANG Yaxian;ZHAO Feng(School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Key Laboratory of Opto Electronic Technology and Intelligent Control of Ministry of Education,Lanzhou 730070,China)
机构地区:[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]光电技术与智能控制教育部重点实验室,兰州730070
出 处:《噪声与振动控制》2020年第6期102-108,共7页Noise and Vibration Control
基 金:甘肃省重点研发计划资助项目(18YF1FA058)。
摘 要:针对直驱永磁同步风电机组(Direct-drive permanent magnet synchronous wind turbine generator,DDPMSG)产生的次同步振荡(Sub synchronous oscillation,SSO)问题,提出基于改进变分模态分解(Variational mode decomposition,VMD)、2阶盲辨识(Second order blind identification,SOBI)和Prony算法相结合的次同步振荡模态辨识方法。首先,利用改进变分模态分解将直驱永磁同步风电机组产生的一组次同步振荡信号作为单通道信号进行分解,得到一组相应的固有模态函数(Intrinsic mode function,IMF);其次,引入盲源分离(Blind source separation,BSS)思想,采用SOBI算法得到完整精确的次同步振荡源信号,并利用Prony算法辨识出该信号的频率、阻尼比和衰减因子。仿真结果表明,对于直驱风电机组产生的次同步振荡信号,该方法能够高效准确辨识出其模态参数,可为次同步振荡抑制问题的研究奠定基础。To solve the problem of sub synchronous oscillation(SSO)caused by direct-drive permanent magnet synchronous wind turbine generators(DDPMSG),a method for SSO mode identification based on improved variational mode decomposition(VMD),second order blind identification(SOBI)and Prony algorithm are proposed.Firstly,the improved VMD is used to decompose a group of SSO signals generated by the DDPMSG as single-channel signals,and the corresponding group of intrinsic mode functions(IMF)is obtained.Secondly,the idea of blind source separation(BSS)is introduced,and the SOBI algorithm is used to obtain the complete and accurate SSO signals.The source signal parameters including frequency,damping ratio and attenuation factor are identified by Prony algorithm.The simulation results show that this method can identify the SSO modal parameters of the DDPMSG quickly and accurately.This work lays a foundation for the research of SSO suppression.
关 键 词:振动与波 变分模态分解 盲源分离 2阶盲辨识 次同步振荡 直驱永磁同步风电机组
分 类 号:TM614[电气工程—电力系统及自动化]
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