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一种基于时频域多特征量的电能质量混合扰动分类新方法

, PP. 83-90

Keywords: 混合扰动,电能质量,改进不完全S变换,特征量,多标签分类

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Abstract:

针对电能质量混合扰动分类问题,提出一种基于时频域多特征量的分类新方法。首先利用聚类经验模型分解方法和改进不完全S变换对扰动信号进行处理,并提取9个时频域特征值;然后,将特征量输入到分块化的自动分类系统中进行扰动识别。该方法充分考虑单一扰动之间的相互干扰,并通过互补的时频域特征量进行有效的抑制。仿真结果表明,在一定的噪声条件下,所提方法可有效分类电压暂降、电压暂升、电压短时中断、脉冲暂态、振荡暂态、谐波和闪变等电能质量扰动及其组合而成的混合扰动。

References

[1]  Shukla S,Mishra S,Sing B. Empirical-mode decomposition with hilbert transform for power-quality assessment[J]. IEEE Transactions on Power Delivery, 2009,24(4):2159-2165.
[2]  Malathi V,Karthikeyan M. Wavelet-support vector machine approach for classification of power quality disturbances[J]. International Journal of Recent Trends in Engineering, 2009,1(3):290-293.
[3]  刘昊,唐轶,冯宇,等. 基于时域变换特性分析的电能质量扰动分类方法[J]. 电工技术学报, 2008,23(11):159-165. Liu Hao,Tang Yi,Feng Yu,et al.A power quality disturbance classification method based on time domain transform characteristic analysis[J].Transactions of China Electrotechnical Society,2008,23(11)
[4]  王丽霞,何正友,戴铭,等. 一种电能质量扰动信号的分层识别新方法[J]. 电力系统自动化, 2009,33(24):65-69. Wang Lixia,He Zhengyou,Dai Ming,et al.A new hieratic power quality disturbance signal identification method[J].Automation of Electric Power Systems,2009,33(24)
[5]  周雒维,管春,卢伟国. 多标签分类法在电能质量复合扰动分类中的应用[J]. 中国电机工程学报, 2011,31(4):45-50. Zhou Luowei,Guan Chun,Lu Weiguo.Application of multi-label classification method to catagorization of multiple power quality disturbances[J].Proceedings of the CSEE,2011,31(4)
[6]  管春. 电能质量综合检测与分析系统研究[D]. 重庆:重庆大学, 2011.Guan Chun.Research on comprehensive power quality detection and analysis systems[D].Chongqing:ChongqingUniversity,2011(in Chinese).
[7]  Biswal B,Dash P K,Panigrahi B K. Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization[J]. IEEE Trans. on Industrial Electronics, 2009,56(1):212-220.
[8]  Chuang C L,Lu Y L,Huang T L,et al. Recognition of multiple PQ disturbances using dynamic structure neural networks,Part 1:theoretical introduction[C]//IEEE/PES Transmission and Distribution Conference and Exhibition. Dalian, China:Institute of Electrical and Electronics Engineers,2005:1-6.
[9]  何为,杨洪耕. 基于第二代小波变换和离散隐马尔可夫模型的电能质量扰动分类[J]. 电工技术学报, 2007,22(5):146-152. He Wei,Yang Honggeng.Disturbance classification based on second generation wavelet transform and discrete hidden Markov models[J].Transactions of China Electrotechnical Society,2007,22(5)
[10]  Lin W M,Wu C H,Lin C H,et al. Detection and classification of multiple power-quality disturbances with wavelet multiclass SVM[J]. IEEE Trans. on Power Delivery, 2008,23(4):2575-2582.
[11]  管春,周雒维,卢伟国. 基于多标签RBF神经网络的电能质量复合扰动分类方法[J]. 电工技术学报, 2011,26(8):198-204. Guan Chun,Zhou Luowei,Lu Weiguo.Recognition of multiple power quality disturbances using multi-label RBF neural networks[J].Transactions of China Electrotechnical Society,2011,26(8)
[12]  IEEE. IEEE Std. 1159?2009 IEEE recommended practice for monitoring electric power quality[S].New York:IEEE, 1995.
[13]  Wu Z,Huang N E. A study of the characteristics of white noise using the empirical mode decomposition method[J]. Proceedings of the Royal Society Lond A, 2004,460:1597-1611.
[14]  Wu Z,Huang N E. Ensemble empirical mode decomposition:a noise-assisted data analysis method[R]. Calverton:Center for Ocean-Land-Atmosphere Studies, 2005.
[15]  Faisal M F,Mohamed A,Hussain A,et al. Support vector regression based s-transform for prediction of single and multiple power quality disturbances[J]. European Journal of Scientific Research, 2009,34(2):237-251.
[16]  Zhao Fengzhan,Yang Rengang. Power quality disturbance recognition using S-transform[J]. IEEE Transactions on Power Delivery, 2007,22(2):944-950.
[17]  易吉良. 基于S变换的电能质量扰动分析[D]. 长沙:湖南大学, 2010.Yi Jiliang.Analysis of power quality disturbances using S-transform[D].Changshang:HunanUniversity,2010(in Chinese).
[18]  占勇,程浩忠,丁屹峰,等. 基于S变换的电能质量扰动支持向量机分类识别[J]. 中国电机工程学报, 2005,25(4):51-56. Zhang Yong,Cheng Haozhong,Ding Yifeng,et al.S-transform based classification of power quality disturbance signals by support vector machines[J].Proceedings of the CSEE,2005,25(4)
[19]  Chilukuri M V,Dash P K. Multiresolution S-transform- based fuzzy recognition system for power quality events[J]. IEEE Transactions on Power Delivery, 2004,19(1):323-330.
[20]  易吉良,彭建春,谭会生. 采用不完全S变换的电能质量扰动检测方法[J]. 高电压技术, 2009,35(10):2562-2567. Yi Jiliang,Peng Jianchun,Tan Huisheng.Detection method of power quality disturbances using incomplete S-transform[J].High Voltage Engineering,2009,35(10)
[21]  高静怀,满蔚仕,陈树民. 广义S变换域有色噪声与信号识别方法[J]. 地球物理学报, 2004,22(5):869-875. Gao Jinghuai,Man Weishi,Chen Shumin.Recognition of signal from colored noise background in generalized S-transform domain[J].Chinese Journal of Geophysics,2004,22(5)
[22]  李立,易吉良,朱建林. 采用改进不完全S变换估计电能质量扰动参数[J]. 电工技术学报, 2011,26(6):187-193. Li Li,Yi Jiliang,Zhu Jianchun.Parameter estimation of power quality disturbances using modified incomplete S-transform[J].Transactions of China Electrotechnical Society,2011,26(6)
[23]  黄奂,吴杰康. 基于经验模态分解的电能质量扰动信号定位方法[J]. 电网技术, 2010,34(5):41-45. Huang Huan,Wu Jiekang.A method to locate power quality disturbing signal based on empirical mode decomposition[J].Power System Technology,2010,34(5)
[24]  Uyar M,Yildirim S,Gencoglu M T. An effective wavelet-based feature extraction method for classification of power quality disturbance signals[J]. Electric Power Systems Research, 2008,78(10):1747-1755.

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