|
|
Identification of anti-aliasing modal parameters for low frequency oscillations based on synchrosqueezing wavelet transform |
Xie Jiaan |
Foshan Power Supply Bureau of Guangdong Power Grid Co., Ltd, Foshan, Guangdong 528000 |
|
|
Abstract In order to solve the problem of incorrect analysis results caused by the aliasing of adjacent frequency components when the empirical mode decomposition (EMD) is used to extract the modes of low frequency oscillation signal (LFO), a novel method based on synchrosqueezing wavelet transform (SST) is introduced to extract the anti-aliasing model parameters of LFO. It applies SST to extract a set of intrinsic mode components without frequency aliasing in LFO signal and calculates the instantaneous parameters including magnitude, frequency and phase of every model function with Hilbert transformation (HT), and then calculates the damping ratio of every model function based on the parameters above and the formulas derived. Thus it realizes effective extraction of all parameters of LFO signal. This method can be adopted to analyze strong non-linear oscillation models in power systems and design damping controllers. The simulation and example analysis results indicate the feasibility and validity of the new method proposed in this paper.
|
Received: 16 March 2019
Published: 19 December 2019
|
|
|
|
Cite this article: |
Xie Jiaan. Identification of anti-aliasing modal parameters for low frequency oscillations based on synchrosqueezing wavelet transform[J]. Electrical Engineering, 2019, 20(12): 28-34.
|
|
|
|
URL: |
http://dqjs.cesmedia.cn/EN/Y2019/V20/I12/28
|
[1] 龚鸿, 江伟, 王渝红, 等. 基于静止同步补偿器与直流调制协调控制的低频振荡抑制方法[J]. 电工技术学报, 2017, 32(6): 67-75. [2] 金涛, 刘对. 基于广义形态滤波与改进矩阵束的电力系统低频振荡模态辨识[J]. 电工技术学报, 2017, 32(6): 3-13. [3] 仲启树, 唐志军, 金涛. 基于部分左特征结构配置的电力系统优化阻尼控制[J]. 电工技术学报, 2018, 33(13): 3012-3022. [4] 罗超, 肖湘宁, 张剑, 等. 并联型有源次同步振荡抑制器阻尼控制策略优化设计[J]. 电工技术学报, 2016, 31(21): 150-158. [5] 赵妍, 李志民, 李天云. 低频振荡模态参数辨识的共振稀疏分解SSI分析方法[J]. 电工技术学报, 2016, 31(2): 136-144. [6] 竺炜, 马建伟, 曾喆昭, 等. 分段傅里叶神经网络的低频振荡模式识别方法[J]. 电力系统保护与控制, 2012, 40(15): 40-45. [7] 侯王宾, 刘天琪, 李兴源. 基于经验模态分解滤波的低频振荡Prony分析[J]. 物理学报, 2010, 59(5): 3531-3537. [8] 肖晋宇, 谢小荣, 胡志祥, 等. 电力系统低频振荡在线辨识的改进Prony算法[J]. 清华大学学报: 自然科学版, 2004, 44(7): 883-887. [9] 芦晶晶, 郭剑, 田芳, 等. 基于Prony方法的电力系统振荡模式分析及PSS参数设计[J]. 电网技术, 2004, 28(15): 31-34, 44. [10] 徐东杰, 贺仁睦, 高海龙. 基于迭代Prony算法的传递函数辨识[J]. 中国电机工程学报, 2004, 24(6): 40-43. [11] 赵妍, 李武璟, 聂永辉. 次同步振荡的频率切片小波变换检测方法[J]. 电工技术学报, 2017, 32(6): 106-114. [12] Rueda J L, Juarez C A, Erlich I.Wavelet-based analysis of power system low-frequency electro- mechanical oscillations[J]. IEEE Transactions on Power Systems, 2011, 26(3): 1733-1743. [13] 李天云, 谢家安, 张方彦, 等. HHT在电力系统低频振荡模态参数提取中的应用[J]. 中国电机工程学报, 2007, 27(28): 79-83. [14] Huang Ne, Shen Z, Long S R, et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A-Mathematical Physical and Engineering Sciences, 1998, 454(1971): 903-995. [15] 喻敏, 王斌, 陈绪轩, 等. 同步挤压小波变换在电力系统低频振荡模态参数提取中的应用[J]. 电工技术学报, 2017, 32(6): 14-20. [16] 喻敏, 王斌, 王文波, 等. 基于SST的间谐波检测方法[J]. 中国电机工程学报, 2016, 36(11): 2944-2951. |
|
|
|