基于原子分解法的中性点不接地系统铁磁谐振检测

doi:10.19595/j.cnki.1000-6753.tces.170078

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (26315 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract According to the characteristics of ferroresonance signal, Atomic Decomposition Method was introduced as the analysis method of power system ferroresonance to overcome deficiency of traditional methods. Atomic Decomposition Method has a strong ability to analyze non-stationary signals.The best matching atoms could accurately characterize the ferroresonancesignal,and also quickly detect the ferroresonance frequency and other parameters. Aiming at the ferroresonance excited by the single-phase instantaneous ground fault and according to the analysis of post fault three-phase voltage and the zero-sequence voltage, the zero-sequence voltage was divided into three groups by time. Based on the relationship between signal frequency and attenuation coefficient, a ferroresonance detection method was proposed to detect the ferroresonance fault and the type of the system. This method could also distinguish the system fault from single-phase permanent earth fault and single-phase instantaneous ground fault. The simulation results showed that the proposed method can accurately detect the ferroresonance fault of the system which verified the effectiveness of the method.

Key words： Atomic decomposition ferroresonance detect isolated neutral system

Received: 17 January 2017 Published: 14 March 2018

PACS:

TM71

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Gong Qingwu
	Zhang Jing
	Lei Jiazhi
	Zhang Caisen
	Li Xun

Cite this article:

Gong Qingwu,Zhang Jing,Lei Jiazhi等. Detection of Ferroresonance in Isolated Neutral System Based on Atomic Decomposition Method[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1114-1124.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.170078 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I5/1114

[1] 陈慈萱. 电气工程基础(下册)[M]. 北京: 中国电力出版社, 2004.
[2] 黄艳玲, 司马文霞, 杨鸣, 等. 实测铁磁谐振时间序列的非线性动力学分析[J]. 电工技术学报, 2016, 31(5): 126-134.
Huang Yanling, Sima Wenxia, Yang Ming, et al.Nonlinear dynamic analysis of the measured ferroresonance time series[J]. Transactions of China Electrotechnical Society, 2016, 31(5): 126-134.
[3] 杨秋霞, 宗伟, 田璧元. 基于小波分析的铁磁谐振检测[J]. 电网技术, 2001, 25(11): 55-57.
Yang Qiuxia, Zong Wei, Tian Biyuan.Detection of ferromagnetic resonance based on wavelet analysis[J]. Power System Technology, 2001, 25(11): 55-57.
[4] 吴骏, 卢刚. 小电流接地系统单相接地与谐振状态辨识技术[J]. 电力系统保护与控制, 2010, 38(13): 144-147.
Wu Jun, Lu Gang.Virtual grounding identification technology in neutral point non-effectively ground system[J]. Power System Technology, 2010, 38(13): 144-147.
[5] 齐郑, 董迪, 杨以涵. 中性点不接地系统铁磁谐振与单相接地辨识技术[J]. 电力系统自动化, 2010, 34(1): 55-58.
Qi Zheng, Dong Di, Yang Yihan.Technique for differentiation between ferroresonance and single-phase-to- earth fault in isolated neutral point system[J]. Automation of Electric Power Systems, 2010, 34(1): 55-58.
[6] 姜杰, 赵广泉, 孙小江. 基于信号注入法的铁磁谐振与单相接地故障辨识[J]. 电测与仪表, 2012, 49(3): 46-49.
Jiang Jie, Zhao Guangquan, Sun Xiaojiang.Distinguish ferroresonance from single-phase earth fault based on the approach of signal injection[J]. Electrical Measurement and Instrumentation, 2012, 49(3): 46-49.
[7] 郝毅, 张艳霞. 基于小波包分频特性的中性点不接地系统铁磁谐振检测[J]. 电网技术, 2006, 30(23): 72-76.
Hao Yi, Zhang Yanxia.Detecion of ferroresonance in neutral non-grounding system based on decomposition characteristic of wavelet packet[J]. Power System Technology, 2006, 30(23): 72-76.
[8] Mallat S G, Zhang Zhifeng.Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12): 3397-3415.
[9] Coifman R R, Wickerhauser M V.Entropy-based algorithms for best basis selection[J]. IEEE Transactions on Information Theory, 1992, 38(2): 713-718.
[10] 董海艳, 贾清泉, 崔志强, 等. 复杂电能质量扰动事件源定位方法[J]. 电工技术学报, 2016, 31(23): 116-124.
Dong Haiyan, Jia Qingquan, Cui Zhiqiang, et al, Source localization method for complex power quality disturbance events[J]. Transactions of China Electrotechnical Society, 2016, 31(23): 116-124.
[11] 王永强, 谢军, 律方成. 基于改进量子粒子群优化稀疏分解的局放信号去噪方法[J]. 电工技术学报, 2015, 30(12): 320-329.
Wang Yongqiang, Xie Jun, Lü Fangcheng.PD signal denoising method based on improved quantum-behaved particle swarm optimization sparse decomposition[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 320-329.
[12] Lopez-Risueno G, Grajal J, Yeste-Ojeda O A. Signal detection and estimation using atomic decomposition and information-theoretic criteria[C]//IEEE International Conference on Acoustics Speech and Signal Processing, Montreal, Canada, 2004: 97-100.
[13] 王成梅. 地震信号稀疏分解快速算法及原子库选择研究[D]. 成都: 西南交通大学, 2010.
[14] 田波, 张葛祥, 龙良将. 基于Chirp原子的雷达辐射源信号无意调制特征提取[J]. 微计算机信息, 2010, 26(11): 223-225.
Tian Bo, Zhang Gexiang, Long Liangjiang.Unintentional modulation feature extraction of radar emitter signals based on Gaussian Chirp atoms[J]. Microcomputer Information, 2010, 26(11): 223-225.
[15] 朱明, 普运伟, 金炜东. 基于时频原子方法的雷达辐射源信号特征提取[J]. 电波科学学报, 2007, 22(3): 458-462.
Zhu Ming, Pu Yunwei, Jin Weidong.Feature extraction of radar emitter signals based on time-frequency atoms[J]. Chinese Journal of Radio Science, 2007, 22(3): 458-462.
[16] 苏玉香, 刘志刚, 李科亮. Hilbert-Huang变换在电气化铁路谐波检测中的应用[J]. 电网技术, 2008, 32(18): 30-35.
Su Yuxiang, Liu Zhigang, Li Keliang.Application of Hilbert-Huang transform in harmonic detection of electrified railway[J]. Power System Technology, 2008, 32(18):30-35.
[17] Wong K P, Pham V L.Analysing power system waveforms using wavelet-transform approach[C]//The 5th International Conference on Advances in Power System Control, Operation and Management, Hong Kong, China, 2000, 2: 500-504.
[18] Wang Ning, Jia Qingquan, Dou Chunxia.Classification of power quality disturbance based on atomic energy[C]//The 2010 International Conference on Modelling,Identification and Control, Okayama, Japan, 2010: 454-459.
[19] 贾晶晶, 龚庆武, 李勋. 采用原子分解法的带并联补偿线路单相自适应重合闸[J]. 电力系统自动化, 2013, 37(5): 117-123.
Jia Jingjing, Gong Qingwu, Li Xun.Research on single-phase adaptive reclose of shunt compensated transmission lines using atomic decomposition[J]. Automation of Electric Power Systems, 2013, 37(5): 117-123.
[20] 李勋, 龚庆武, 贾晶晶. 采用原子分解能量熵的低频振荡主导模式检测方法[J]. 中国电机工程学报, 2012, 32(1): 131-139.
Li Xun, Gong Qingwu, Jia Jingjing.A detection method for low frequency oscillation dominant modes based on atomic decomposition energy entropy[J]. Proceedings of the CSEE, 2012, 32(1): 131-139.
[21] 李勋, 龚庆武, 贾晶晶, 等. 基于原子稀疏分解的低频振荡模态参数辨识方法[J]. 电工技术学报, 2012, 27(9): 124-133.
Li Xun, Gong Qingwu, Jia Jingjing, et al.Atomic sparse decomposition based identification method for low-frequency oscillation modal parameters[J]. Transactions of China Electrotechnical Society, 2012, 27(9): 124-133.
[22] 李勋, 龚庆武, 关钦月, 等. 基于PSO的模态原子法在低频振荡模式时变特性追踪的应用[J]. 中国电机工程学报, 2013, 33(10): 79-89.
Li Xun, Gong Qingwu, Guan Qinyue, et al.PSO based modal atom method and its application to track time-varying performance of low frequency oscillation modes[J]. Proceedings of the CSEE, 2013, 33(10): 79-89.
[23] 王宁, 李林川, 贾清泉. 应用原子分解的电能质量扰动信号分类方法[J]. 中国电机工程学报, 2011, 31(4): 51-58.
Wang Ning, Li Linchuan, Jia Qingquan.Classification of power quality disturbance signals using atomic decomposition method[J]. Proceedings of the CSEE, 2011, 31(4): 51-58.
[24] Ghofrani S, Ayatollahi A, McLernon D C. A comparison of different time-frequency atoms in both ambiguity and time-frequency domains[C]//Proceedings of the 3rd International Symposium on Image and Signal Processing, Aizu, Japan, 2003: 158-161.
[25] Lovisolo L, Silva E A B D. Efficient coherent adaptive representation of monitored electric signals in power systems using damped sinusoids[J]. IEEE Transactions on Signal Processing, 2005, 53(10): 3831-3846.
[26] Ekanadham C, Tranchina D, Simoncelli E P.Recovery of sparse translation-invariant signals with continuous basis pursuit[J]. IEEE Transactions on Signal Processing, 2011, 59(10): 4735-4744.
[27] Kennedy J, Eberhart R C.Particle swarm optimization[C]//Proceedings of the 4th IEEE International Conference on Neural Networks, Piscataway, 1995: 1942-1948.
[28] Eberhart R, Kennedy J.A new optimizer using particle swarm theory[C]//The 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995: 39-43.
[29] 石启新, 谈顺涛. 基于Matlab的电压互感器铁磁谐振数字仿真[J]. 高电压技术, 2004, 30(8): 25-27.
Shi Qixin, Tan Shuntao.Digital simulation analysison ferroresonance of electromagnetic potential transformer based on MATLAB[J]. High Voltage Engineering, 2004, 30(8): 25-27.
[30] 平绍勋. 电力系统内部过电压保护[M]. 北京: 中国电力出版社, 2006.