An Identification Method Based on Improved Prony for Fast Attenuate Component of the Power System Low-Frequency Oscillation

doi:10.11985/2018.12.007

Abstract

Abstract:

Considering that the traditional Prony algorithm is very difficult to analyze the fast attenuate component of the power system low frequency oscillation mode and the fast attenuate component can be missed easily, an improved method of extracting rapid attenuate signal is proposed which is called Prony segment analysis method based on Givens transform. This method divides the data acquisition time into two periods, and the second period is analyzed firstly to calculate the slow attenuate component, then the first period is analyzed for calculating the fast attenuate component. Numerical example proves that this algorithm can accurately extract fast attenuate component of low frequency oscillation mode, and also makes the slow attenuate component more accurate.

Key words: Low frequency oscillation, Prony method, fast attenuation, Givens transform, segment analysis, accuracy

CLC Number:

TM74

Mu Jianwei,Shang Yanan,Liu Wengang,Dai Siyuan,Jiang Peng,Wang baili,Wang Yanbo. An Identification Method Based on Improved Prony for Fast Attenuate Component of the Power System Low-Frequency Oscillation[J]. Journal of Electrical Engineering, 2018, 13(12): 36-41.

Figures/Tables 4

Fig.111

Tab.1

Tab.2

Tab.3

References 16

[1]	Calderon-Guizar J G, Ramirez-Gonzalez M, Castellanos-Bustamante R, et al. Identification and monitoring inter-area oscillations in power systems [C].IEEE Trans. Power Tech., Eindhoven, 2015: 1-6.
[2]	郑武 . 短时傅里叶变换在火成岩裂缝中的测井评价方法研究[D]. 吉林:吉林大学, 2016.
[3]	孙庆森, 张海峰, 王猛 , 等. 小波算法在变压器励磁涌流中的应用研究[J]. 电力系统保护与控制, 2017,45(8):121-125.
	Sun Qingsen, Zhang Haifeng, Wang Meng , et al. Application of wavelet algorithms in transformer inrush current[J]. Power System Protection and Control, 2017,45(8):121-125.
[4]	陈国雄 . 基于分形与小波理论的成矿复杂信息提取与识别方法研究[D]. 北京:中国地质大学, 2016.
[5]	胡昊明, 郑伟, 徐伟 , 等. Prony和HHT算法在低频振荡在线辨识中的适用性比较[J]. 电力系统保护与控制, 2013,41(14):33-40. doi: 10.7667/j.issn.1674-3415.2013.14.006
	Hu Haoming, Zheng Wei, Xu Wei , et al. Applicability comparison of Prony and HHT algorithms in on-line identification of low-frequency oscillations[J]. Power System Protection and Control, 2013,41(14):33-40. doi: 10.7667/j.issn.1674-3415.2013.14.006
[6]	杨德昌 , Rehtanz C, 李勇,等.基于改进希尔伯特-黄变换算法的电力系统低频振荡分析[J]. 中国电机工程学报, 2011,31(10):102-108.
	Yang Dechang, Rehtanz C, Li Yong , et al. Low-frequency oscillation analysis of power system based on improved Hilbert-Huang transform[J]. Proceedings of CSEE, 2011,31(10):102-108.
[7]	李天云, 高磊, 赵妍 . 基于HHT的电力系统低频振荡分析[J]. 中国电机工程学报, 2006,26(14):24-30.
	Li Tianyun , Gao Lei and Zhao Yan. Low-frequency oscillation analysis of power system based on HHT[J]. Proceedings of CSEE, 2006,26(14):24-30.
[8]	Hauer J F, Demeure C J, Scharf L L . Initial results in prony analysis of power system response signals[J]. IEEE Trans. Power Systems, 1990,5(1):80-89. doi: 10.1109/59.49090
[9]	Grund C E, Paserba J J, Hauer J F , et al. Comparison of Prony and eigenanalysis for power system control design[J]. IEEE Trans. Power Systems, 1993,8(3):964-971. doi: 10.1109/59.260905
[10]	李安娜, 吴熙, 蒋平 , 等. 基于形态滤波和Prony算法的低频振荡模式辨识的研究[J]. 电力系统保护与控制, 2015,43(3):137-142. doi: 10.7667/j.issn.1674-3415.2015.03.022
	Li Anna, Wu Xi, Jiang Ping , et al. Research on low frequency oscillation mode identification based on morphological filtering and Prony algorithm[J]. Power System Protection and Control, 2015,43(3):137-142. doi: 10.7667/j.issn.1674-3415.2015.03.022
[11]	张晓威, 牛晓红, 翟广锐 . 改进的Prony算法在多正弦信号频率估计中的应用研究[J]. 电力系统保护与控制, 2017,45(15):140-145.
	Zhang Xiaowei, Niu Xiaohong, Zhai Guangrui . Application of improved Prony algorithm in frequency estimation of multi-sinusoidal signals[J]. Power System Protection and Control, 2017,45(15):140-145.
[12]	邢志斌, 李姗姗, 王伟 , 等. 利用垂线偏差计算高程异常差法方程的快速构建方法[J]. 武汉大学学报(信息科学版), 2016,41(6):778-783. doi: 10.13203/j.whugis20140491
	Xing Zhibin, Li Shanshan, Wang Wei , et al. Fast construction method of normal equation for calculating elevation anomaly difference by vertical deviation[J]. Journal of Wuhan University (Information Science Edition), 2016,41(6):778-783. doi: 10.13203/j.whugis20140491
[13]	黄德伦, 史经俭, 廉琦 , 等. 基于法方程病态的谱修正迭代算法的探讨[J]. 测绘科学, 2013,38(2):35-37.
	Huang Delun, Shi Jingjian, Lian Qi , et al. Exploration of spectral correction iteration algorithm based on normal equation morbidity[J]. Surveying and Mapping Science, 2013,38(2):35-37.
[14]	魏子卿 . 用Givens变换解最小二乘问题[J]. 测绘工程, 1996,5(2):1-7.
	Wei Ziqing . Solving the least square problem by givens transform[J]. Surveying and Mapping Engineering, 1996,5(2):1-7.
[15]	Pandian A, Parthasarathy K , et al. Towards faster givens rotations based power system state estimator[J]. IEEE Trans. Power Systems, 1999,14(3):837-843. doi: 10.1109/59.780893
[16]	杜鹃, 冯思臣 . 复矩阵的Givens变换及其qr分解[J]. 成都理工大学学报(自然科学版), 2011,38(6):693-696.
	Du Juan, Feng Sichen . Givens transformation of complex matrix and its QR decomposition[J]. Journal of Chengdu University of Technology (Natural Science Edition), 2011,38(6):693-696.

分量序号	频率f/Hz	衰减因子α	幅值A	初相θ/(°)
1	0.423 0	-0.002 7	10.000 0	110.000 0
2	0.420 0	-0.265 2	2.000 0	13.000 0
3	0.247 3	-0.031 1	10.000 0	20.000 0
4	1.034 9	-0.293 6	1.000 0	60.000 0
5	2.400 0	-45.878 8	5.800 0	10.000 0
6	0.900 0	-55.115 6	6.300 0	60.000 0

分量序号	方法	频率f/Hz	衰减因子α	幅值A	初相θ/(°)
1	Givens变换	0.423 0	-0.002 7	10.000 0	110.000 0
1	法方程形式	0.423 0	-0.002 7	9.999 9	109.999 3
2	Givens变换	0.420 0	-0.265 2	2.000 0	13.000 0
2	法方程形式	0.420 0	-0.265 2	1.999 8	13.000 9
3	Givens变换	0.247 3	-0.031 1	10.000 0	20.000 0
3	法方程形式	0.247 3	-0.031 1	10.000 0	20.000 0
4	Givens变换	1.034 9	-0.293 6	1.000 0	60.000 0
4	法方程形式	1.034 9	-0.293 6	1.000 0	60.000 0
5	Givens变换	2.400 0	-45.878 7	5.800 1	9.999 1
5	法方程形式	2.365 9	-45.923 0	6.214 1	12.011 8
6	Givens变换	0.900 0	-55.115 8	6.300 1	60.002 8
6	法方程形式	1.528 5	-56.554 5	2.421 7	60.193 5

分量序号	方法	频率f/Hz	衰减因子α	幅值A	初相θ/(°)
1	分段	0.423 0	-0.002 7	10.000 0	110.000 0
1	不分段	0.423 0	-0.002 7	10.000 0	110.000 0
2	分段	0.420 0	-0.265 2	2.000 0	13.000 0
2	不分段	0.420 0	-0.265 2	2.000 0	13.000 0
3	分段	0.247 3	-0.031 1	10.000 0	20.000 0
3	不分段	0.247 3	-0.031 1	10.000 0	20.000 0
4	分段	1.034 9	-0.293 6	1.000 0	60.000 0
4	不分段	1.0349	-0.2936	1.0000	60.000 0
5	分段	2.400 0	-45.878 7	5.800 1	9.999 1
5	不分段	2.426 6	-46.663 1	7.693 8	4.600 2
6	分段	0.900 0	-55.115 8	6.300 1	60.002 8
6	不分段	–	–	–	–