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作 者:孙东阳[1] 焦英姿 孟繁易 王帅[2] 孙力[2] SUN Dongyang;JIAO Yingzi;MENG Fanyi;WANG Shuai;SUN Li(School of Electrical and Electronic Engineering,Harbin University of Science and Technology,Harbin 150080,China;School of Electrical Engineering and Automation,Harbin Institute of Technology,Harbin 150001,China)
机构地区:[1]哈尔滨理工大学电气与电子工程学院,黑龙江哈尔滨150080 [2]哈尔滨工业大学电气工程及自动化学院,黑龙江哈尔滨150001
出 处:《电机与控制学报》2024年第12期82-96,共15页Electric Machines and Control
基 金:黑龙江省“优秀青年教师基础研究支持计划”(YQJH2023254)。
摘 要:电网发生次同步振荡(SSO)时,会对构网型直驱永磁风力发电机(D-PMSG)网侧变流器的控制性能造成不利影响,进而威胁到整个系统的稳定性。为了解决这一问题,提出一种基于自适应陷波器(ANF)的SSO抑制策略。首先,深入分析SSO对基于虚拟同步机的构网型D-PMSG网侧控制的影响机理,明确扰动在系统中的传播路径,并研究SSO特性变化对陷波器抑制功能的影响。随后,针对固定参数陷波器在面对SSO频率时变特性时的局限性,研究一种基于改进快速傅里叶变换的SSO参数辨识算法,以实现对SSO频率的实时追踪。在此基础上,设计一种根据参数辨识结果动态更新ANF中心频率的策略,并确定ANF在控制系统中的最佳介入位置,以优化抑制效果。最后,通过搭建仿真模型及实验平台,分析验证所提控制策略对SSO的抑制效果。Sub-synchronous oscillation(SSO)occurring in power grid can adversely affect the control performance of grid-side converter for grid-forming direct-drive permanent magnet synchronous generators(D-PMSG),thus threatening the stability of entire system.An SSO suppression strategy based on an adaptive notch filter(ANF)was proposed to address this issue.The impact mechanism of SSO on the grid-side control of D-PMSG based on virtual synchronous generators was analyzed thoroughly.Meanwhile,the propagation path of disturbances within the system was clarified.Also,the influence of SSO characteristic variation on the notch filter’s suppression function was studied.Subsequently,an SSO parameter identification algorithm based on an improved fast Fourier transform was developed to address the limitations of fixed-parameter notch filters when dealing with the time-varying characteristics of SSO frequencies,enabling real-time tracking of SSO frequencies.On this basis,a strategy for dynamically updating the ANF center frequency according to parameter identification results was designed,and the optimal intervention position of ANF in the control system was determined to optimize suppression effects.Finally,the suppression effect of the proposed control strategy on SSO was analyzed and verified through the construction of simulation models and experimental platforms.
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