摘要
提出基于滑窗FFT(快速傅立叶变换)的次同步振荡时变幅频监测方法,对振荡信号的时变模态参数进行在线辨识。首先采用加窗插值方法减少频谱泄露和栅栏效应,降低FFT辨识误差。然后,通过时间窗的滑动对每个时间窗截取的信号进行FFT,得到振荡频率和振荡幅值的动态序列,即频率和幅值随时间变化关系,通过对时变振荡幅值的分析计算得到衰减因子的动态序列。最后,以理想非平稳信号、仿真信号及电网实测信号作为测试算例,通过与Prony和HHT算法的对比分析,表明该方法不仅不受模态混叠现象影响,而且具有一定抗噪能力,能够有效辨识随机时变振荡模态,实现次同步振荡在线监测分析。
This paper proposes a time-varying amplitude frequency monitoring method based on sliding window FFT of subsynchronous oscillation to identify the time-varying modal parameters of the oscillating signals on-line.Firstly,windowed interpolation methods are used to reduce the spectral leakage and fence effect,and decrease the FFT identification errors.Then,through the sliding of the time windows,the signals intercepted by each time window is transformed through FFT to obtain a dynamic sequence of oscillation frequency and oscillation amplitude,that is,varying frequency and amplitude with time.The dynamic sequence of the damping factors is obtained by analyzing and calculating the time-varying oscillation amplitude.Finally,using the ideal non-stationary signals,simulation signals and the measured signals of the power grid as test cases,the comparison results with the Prony and HHT algorithms show that this method not only can eliminate the influence of modal mixing,but also has anti-noise ability.The method can effectively identify the random time-varying oscillation modes and achieve on-line monitoring and analysis of sub-synchronous oscillations.
作者
杨京
王彤
唐俊刺
YANG Jing;WANG Tong;TANG Junci(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China;State Grid Liaoning Electric Power Supply Co.Ltd.,Shenyang 110006,China)
出处
《中国电力》
CSCD
北大核心
2020年第11期139-146,共8页
Electric Power
基金
国家自然科学基金资助项目(基于智能电网多维信息融合的系统安全保护研究,51637005)
国家电网有限公司总部科技项目(系统保护动作行为全过程智能分析、控制决策与评价关键技术研究)。
关键词
次同步振荡
时变幅频
模态辨识
滑窗
FFT
sub-synchronous oscillation
time-varying amplitude frequency
modal identification
sliding window
FFT
