环境激励与小幅持续周期扰动表现特征及统计学分析

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Abstract The system response is similar to the small fluctuations in noise because of ambient excitations, such as random fluctuations of renewable energy outputs and the switching of loads. If the magnitude of periodic perturbation is small, it might be submerged in the random responses undergoing ambient excitations. This paper derives the mathematical expressions of the dynamic responses undergoing slight sustained periodic disturbance and ambient excitation. And then the related mechanism of active power characterization was explained from a mathematical point-of-view. Based on sliding Kurtosis method (SKM), a method for slight sustained periodic disturbance detection was proposed according to the statistical characteristics of dynamic response undergoing slight sustained periodic disturbance and ambient excitation. Firstly, the fourth moment and the variance of the active power of tie line were analyzed, and then the corresponding Kurtosis was calculated. Finally, the slight sustained periodic disturbance can be detected by quantitative comparisons of the kurtosis results. Simulations in 4-machine 2-area system and 16-machine 68-bus system have verified the proposed method.

Key words： Ambient excitation periodic disturbance sliding Kurtosis method statistical characteristics

Received: 22 May 2016 Published: 29 March 2017

PACS:

TM721

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	Yang Deyou
	Wang Lixin
	Cai Guowei

Cite this article:

Yang Deyou,Wang Lixin,Cai Guowei. The Statistical Characteristics of Response Undergoing Slight Sustained Periodic Disturbance and Ambient Excitation[J]. Transactions of China Electrotechnical Society, 2017, 32(6): 41-48.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I6/41

[1] 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.
Zhao Yan, Li Zhimin, Li Tianyun. Low frequency oscillation modal parameter identification using resonance-based sparse signal decomposition and SSI method[J]. Transactions of China Electrotechnical Society, 2016, 31(2): 136-144.
[2] 李安娜, 吴熙, 蒋平. 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.
Li Anna, Wu Xi, Jiang Ping. Research on identifying low frequency oscillation modes based on morpholo- gical filtering theory and Prony algorithm[J]. Power System Protection and Control, 2015, 43(3): 137-142.
[3] 陈恩泽, 刘涤尘, 廖清芬, 等. 多重扰动下的跨区电网低频振荡研究[J]. 电工技术学报, 2014, 29(2): 290-296.
Chen Enze, Liu Dichen, Liao Qingfen, et al. Research on low frequency oscillation of interconnected power grid based on multiple disturbances[J]. Transactions of China Electrotechnical Society, 2014, 29(2): 290-296.
[4] 项丽, 鲍颜红, 耿天翔, 等. 基于广域信息的发电机电压控制抑制区间低频振荡方法[J]. 电力系统保护与控制, 2015, 43(18): 18-22.
Xiang Li, Bao Yanhong, Geng Tianxiang, et al. Damping inter-area low frequency oscillations method for generator voltage control based on wide- area information[J]. Power System Protection and Control, 2015, 43(18): 18-22.
[5] 李莹, 贾文双, 李文峰, 等. 基于起振波形在线判别电力系统功率振荡性质[J]. 中国电机工程学报, 2013, 33(25): 54-60.
Li Ying, Jia Wenshuang, Li Wenfeng, et al. Online identification of power oscillation properties based on the initial period of wave[J]. Proceedings of the CSEE, 2013, 33(25): 54-60.
[6] 赵妍, 李志民, 李天云. 电力系统低频振荡监测的Duffing振子可停振动系统法[J]. 电工技术学报, 2015, 30(20): 159-167.
Zhao Yan, Li Zhimin, Li Tianyun. Duffing oscillator order stopping oscillation system method for moni- toring of low-frequency oscillation in power system[J]. Transactions of China Electrotechnical Society, 2015, 30(20): 159-167.
[7] 余一平, 闵勇, 陈磊, 等. 基于能量函数的强迫功率振荡扰动源定位[J]. 电力系统自动化, 2010, 34(5): 1-6.
Yu Yiping, Min Yong, Chen Lei, et al. Disturbance source location of forced power oscillation using energy functions[J]. Automation of Electric Power Systems, 2010, 34(5): 1-6.
[8] 李阳海, 黄莹, 刘巨, 等. 基于阻尼转矩分析的电力系统低频振荡源定位[J]. 电力系统保护与控制, 2015, 43(14): 84-91.
Li Yanghai, Huang Ying, Liu Ju, et al. Power system oscillation source location based on damping torque analysis[J]. Power System Protection and Control, 2015, 43(14): 84-91.
[9] Follum J, John W. Detection of periodic forced oscillations in power systems[J]. IEEE Transactions on Power Systems, 2015, 31(3): 1-11.
[10] Zhou N. A cross-coherence method for detecting oscillation[J]. IEEE Transactions on Power Systems, 2016, 31(1): 623-631.
[11] Zhou N, Jeff Dagle. Initial results in using a self- coherence method for detecting sustained oscilla- tions[J]. IEEE Transactions on Power Systems, 2015, 30(1): 522-530.
[12] Wang X Z, Konstantin T. Data-driven diagnostics of mechanism and source of sustained oscillations[J]. IEEE Transactions on Power Systems, 2015, 17(4): 401-407.
[13] 宋燕. 二阶常系数非齐次线性微分方程的通解形式[J]. 高等数学研究, 2011, 14(3): 6-7.
Song Yan. General solution of second order non- homogeneous LDE with constant coefficients[J]. Studies in College Mathematics, 2011, 14(3): 6-7.
[14] 陆大金, 张颢. 随机过程及其应用[M]. 2版. 北京:清华大学出版社, 2012.
[15] Jerome A, Randall R B. The spectral Kurtosis: application to the vibratory surveillance and diag- nostics of roating machines[J]. Mechanical Systems and Signal Processing, 2006, 20(2): 308-331.
[16] 杨富春, 周晓军, 张志刚. 基于滑动峰态算法的信号弱冲击特征提取及应用[J]. 振动与冲击, 2009, 28(4): 103-109.
Yang Fuchun, Zhou Xiaojun, Zhang Zhigang. A new method for extracting weak impulse characteristic based on a sliding Kurtosis algorithm[J]. Journal of Vibration and Shock, 2009, 28(4): 103-109.
[17] Kundar P. Power system stability and control[M]. New York, USA: McGraw-Hill, 1994.