Power system low-frequency oscillation characteristic analysis based on Prony moving average window algorithm

被引：0
|
作者：
Zhang J. [1 ]
Yang T. [2 ]
Chen M. [2 ]
Zhang T. [2 ]
Xiao J. [2 ]
Mao C. [2 ]
机构：
[1] Electric Power Research Institute of Guangdong Power Grid Corporation, Guangzhou
[2] College of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan
来源：
| 2018年 / Electric Power Automation Equipment Press卷 / 38期
关键词：
Electric power systems; Low-frequency oscillation; Moving average window; Prony algorithm; SNR;
D O I：
10.16081/j.issn.1006-6047.2018.10.028
中图分类号：
学科分类号：
摘要：
Prony algorithm can identify related characteristic parameters of power system according to the measured data, which can help to analyze the low-frequency oscillations of the system. However, the traditional Prony algorithms are sensitive to noise and can only analyze partial of the data. A Prony moving average window algorithm is proposed to analyze the data in separate windows, which can not only make full use of the data, but also weaken the noise and obtain correct identification results even if the SNR(Signal-to-Noise Ratio) is very small. The simulative results based on PSASP software verify the accuracy of the Prony moving average window algorithm. © 2018, Electric Power Automation Equipment Press. All right reserved.
引用
收藏
页码：178 / 183
页数：5
相关论文
共 20 条
  • [1] Dong H., Liu D., Zou J., Analysis of power system low frequency oscillation based on Prony algorithm, High Voltage Engineering, 32, 6, pp. 97-100, (2006)
  • [2] Amano M., Watanabe M., Anjo M., Self-testing and self-tuning of power system stabilizers using Prony analysis, IEEE Power Delivery, 18, 5, pp. 38-47, (1998)
  • [3] Wang J., Xia L., Wu Z., Et al., Analysis of power system transient signal based on improved Prony algorithm, Electric Power Automation Equipment, 32, 7, (2012)
  • [4] Tian L., Li C., Liu J., Theory and implemen-tation of visualized online low-frequency oscillation monitoring, Electric Power Automation Equipment, 30, 5, pp. 28-33, (2010)
  • [5] Ma J., Zhang P., Fu H., Et al., Application of phasor measurement unit on locating disturbance source for low-frequency oscillation, IEEE Transactions on Smart Grid, 1, 3, pp. 340-346, (2010)
  • [6] Zhang B., Sun H., Wu W., Et al., Future development of control center technologies for smart grid, Automation of Electric Power Systems, 33, 17, pp. 21-28, (2009)
  • [7] Guo C., Li Q., Wang D., Wide-area Prony analysis of low frequency oscillation in interconnected power system, Electric Power Automation Equipment, 29, 5, pp. 69-73, (2009)
  • [8] Xiong J., Prony analysis of electromechanical oscillation based on PMU and local online supervisory system, (2006)
  • [9] Liu S., Zhao S., Yu Z., Et al., Prony analysis of low frequency oscillation based on wavelet pretreatment technology, Electric Power Automation Equipment, 27, 4, (2007)
  • [10] Zhu W., Tang Y., Zhou Y., Et al., Identification of power system low frequency oscillation mode based on improved Prony algorithm, Power System Technology, 33, 5, (2009)
12