Distortion Waveform m-sequence Dynamic Test Signal Modeling and Compressive Measurement for Electric Energy
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摘要: 为解决非线性动态负荷条件下,智能电能表的动态误差测试问题.本文首先将m序列算子作为映射算子,采用基于信号特性建模的方法,建立三相畸变波形m序列动态测试信号结构化参数模型.其次根据压缩检测(Compressed measurement,CM)理论,采用系统稳态优化的方法构造最优压缩检测测量矩阵,实现对动态测试功率信号电能量值的检测.仿真实验表明,压缩检测方法可以对畸变波形m序列动态测试信号进行电能量值的检测,检测算法的相对误差优于1×10-13.Abstract: To solve the problem of dynamic error measurement of smart energy meter under nonlinear dynamic loading conditions, firstly, we consider the m-sequence operator as a mapping operator and establish a structural model of three-phase distortion waveform m-sequence dynamic test signal using the method base on the load features. Then, according to compressive measurement, we construct the optimal measurement matrix by means of system steady-state optimization to realize the electrical energy measurement. Finally, numerical simulations are performed to prove the reliability of the compressed measurement (CM) method, the relative errors of the measurement algorithm being superior to 1×10-13.1) 本文责任编委 辛景民
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谐波 电流幅值(%) 电压幅值(%) 1 100 100 3 10 10 5 2.6 4.0 7 1.9 3.2 9 0.5 2.8 表 2 IEC62052-11中尖顶波谐波成分
Table 2 Harmonic components of peaked waveform in standard IEC62052-11
谐波 电流幅值(%) 相位 电压幅值(%) 相位 1 100 0 100 0 3 3.8 0 30 180 5 2.4 180 18 0 7 1.7 0 14 180 11 1.1 0 9 180 13 0.8 180 5 0 表 3 IEC62052-11中多个过电流零点谐波成分
Table 3 Harmonic components of multiple zero crossing current waveform in standard IEC62052-11
谐波 电流幅值(%) 相位 电压幅值(%) 相位 1 100 0 100 0 3 0 0 $5\pm 1$ $90\pm2$ 5 0 0 $18\pm2$ $-160\pm2$ 7 0 0 $10\pm2$ $110\pm2$ 11 0 0 $66\pm3$ $130\pm2$ 13 0 0 $50\pm3$ $50\pm2$ -
[1] 蒲诚. 脉冲压缩编码激励超声气体流量测量研究[博士学位论文], 天津大学, 中国, 2010. http://cdmd.cnki.com.cn/Article/CDMD-10056-1013004726.htmPu Cheng. Research on Ultrasonic Gas Flow Metering with Pulse Compression Coded Excitations[Ph. D. dissertation], Tianjin University, China, 2010. http://cdmd.cnki.com.cn/Article/CDMD-10056-1013004726.htm [2] 韩海涛, 马红光, 韩琨, 郑耿乐.关于Volterra频域核辨识的多音激励信号设计.工程设计学报, 2012, 19(2):123-127 http://www.cnki.com.cn/Article/CJFDTotal-GCSJ201202012.htmHan Hai-Tao, Ma Hong-Guang, Han Kun, Zheng Geng-Le. Multitone stimulus signal design for identifying Volterra frequency domain kernels. Chinese Journal of Engineering Design, 2012, 19(2):123-127 http://www.cnki.com.cn/Article/CJFDTotal-GCSJ201202012.htm [3] 刘中坡, 吕西林, 王栋, 乌建中.非线性能量阱刚度优化计算与振动台试验.振动与冲击, 2012, 32(20):77-84 http://www.cqvip.com/QK/95775X/201315/1005353432.htmlLiu Zhong-Po, Lv Xi-Lin, Wang Dong, Wu Jian-Zhong. Stiffness optimization of nonlinear energy sink and shaking table test. Journal of Vibration and Shock, 2012, 32(20):77-84 http://www.cqvip.com/QK/95775X/201315/1005353432.html [4] 孙桥, 王建林, 胡红波, 白杰.低g值冲击加速度的激光绝对法校准.计量学报, 2015, 36(2):145-148 http://d.wanfangdata.com.cn/Periodical_jlxb98201502009.aspxSun Qiao, Wang Jian-Lin, Hu Hong-Bo, Bai Jie. Primary low g shock acceleration calibration using laser interferometry. Acta Metrologica Sinica, 2015, 36(2):145-148 http://d.wanfangdata.com.cn/Periodical_jlxb98201502009.aspx [5] Xu L J, Li X M. Dual-channel pseudorandom sequence generator with precise time delay between its two channels. IEEE Transactions on Instrumentation and Measurement, 2008, 57(12):2880-2884 doi: 10.1109/TIM.2008.926427 [6] Georgakopoulos D, Wright P S. Exercising the dynamic range of active power meters under nonsinusoidal conditions. IEEE Transactions on Instrumentation and Measurement, 2007, 56(2):369-372 doi: 10.1109/TIM.2007.890596 [7] Cataliotti A, Cosentino V, Lipari A, Nuccio S. Metrological characterization and operating principle identification of static meters for reactive energy:an experimental approach under nonsinusoidal test conditions. IEEE Transactions on Instrumentation and Measurement, 2009, 58(5):1427-1435 doi: 10.1109/TIM.2008.2009134 [8] Ferrero A, Prioli M, Salicone S. A metrological comparison between different methods for harmonic pollution metering. IEEE Transactions on Instrumentation and Measurement, 2012, 61(11):2972-2981 doi: 10.1109/TIM.2012.2193700 [9] 陆祖良, 王磊, 李敏.对电能表动态测量功能评价的讨论.电测与仪表, 2010, 47(4):1-4 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dcyyb201004001Lu Zu-Liang, Wang Lei, Li Min. Discussion for evaluation of dynamic measurement function of electrical energy meter. Electrical Measurement and Instrumentation, 2010, 47(4):1-4 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dcyyb201004001 [10] 李世松, 赵伟.基于DDS信号发生器的智能电表动态测量功能评估方法初探.电测与仪表, 2010, 47(10):1-5 doi: 10.3969/j.issn.1001-1390.2010.10.001Li Shi-Song, Zhao Wei. A method for dynamic measurement capabilities evaluation of smart meter based on DDS signal generator. Electrical Measurement and Instrumentation, 2010, 47(10):1-5 doi: 10.3969/j.issn.1001-1390.2010.10.001 [11] 王学伟, 贾晓璐, 王琳, 陆以彪, 孙洋.电能表动态误差特性实验研究.电测与仪表, 2013, 50(12):1-4 http://mall.cnki.net/magazine/Article/DCYQ201608015.htmWang Xue-Wei, Jia Xiao-Lu, Wang Lin, Lu Yi-Biao, Sun Yang. Experimental research for dynamic error characteristic of electrical energy meter. Journal of Electrical Measurement and Instrumentation, 2013, 50(12):1-4 http://mall.cnki.net/magazine/Article/DCYQ201608015.htm [12] 王学伟, 温丽丽, 贾晓璐, 王琳, 王秋月, 袁瑞铭, 周丽霞.智能电能表动态误差的OOK激励测试方法.电力自动化设备, 2014, 34(9):143-147 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dlzdhsb201409024Wang Xue-Wei, Wen Li-Li, Jia Xiao-Lu, Wang Lin, Wang Qiu-Yue, Yuan Rui-Ming, Zhou Li-Xia. OOK driven dynamic error measurement of smart energy meter. Journal of Electric Power Automation Equipment, 2014, 34(9):143-147 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dlzdhsb201409024 [13] Petersen H M, Koch R G, Swart P H, Van Heerden R. Modelling arc furnace fliceker and investigating compensation techniques. In: Proceedings of the 13th IEEE Industry Applications Conference. Orlando, USA: IEEE, 1995. 1733-1740 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=530515 [14] 康婕. 电气化铁路牵引负荷的概论分布模型及其应用[硕士学位论文], 西南交通大学, 中国, 2008. http://cdmd.cnki.com.cn/Article/CDMD-10613-1011235089.htmKang Jie. Probability Distribution Model of Electrified Railway, Straction Load[Master thesis], Southwest Jiaotong University, China, 2008. http://cdmd.cnki.com.cn/Article/CDMD-10613-1011235089.htm [15] Davenport M A, Boufounos P T, Wakin M B, Baraniuk R G. Signal processing with compressive measurements. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(2):445-460 doi: 10.1109/JSTSP.2009.2039178 [16] Shafiul Alam S M, Natarajan B, Pahwa A. Distribution grid state estimation from compressed measurements. IEEE Transactions on Smart Grid, 2014, 5(4):1631-1642 doi: 10.1109/TSG.2013.2296534 [17] Du Z H, Chen X F, Zhang H, Miao H H, Guo Y J, Yang B Y. Feature identification with compressive measurements for machine fault diagnosis. IEEE Transactions on Instrumentation and Measurement, 2016, 65(5):977-987 doi: 10.1109/TIM.2016.2521223 [18] Romero D, Leus G. Wideband spectrum sensing from compressed measurements using spectral prior information. IEEE Transactions on Signal Processing, 2013, 61(24):6232-6246 doi: 10.1109/TSP.2013.2283473 [19] 荆楠, 毕卫红, 胡正平, 王林.动态压缩感知综述.自动化学报, 2015, 41(1):22-37 http://www.aas.net.cn/CN/abstract/abstract18580.shtmlJing Nan, Bi Wei-Hong, Hu Zheng-Ping, Wang Lin. A survey on dynamic compressed sensing. Acta Automatica Sinica, 2015, 41(1):22-37 http://www.aas.net.cn/CN/abstract/abstract18580.shtml [20] Ramirez A, Arguello H, Arce G R, Sadler B M. Spectral image classification from optimal coded-aperture compressive measurements. IEEE Transactions on Geoscience and Remote Sensing, 2012, 52(6):3299-3309 http://ieeexplore.ieee.org/document/6841045/ [21] Atia G K. Change detection with compressive measurements. IEEE Signal Processing Letters, 2015, 22(2):182-186 doi: 10.1109/LSP.2014.2352116 [22] Zahedi R, Krakow L W, Chong E K P, Pezeshki A. Adaptive compressive measurement design using approximate dynamic programming. In: Proceedings of the 2013 American Control Conference. Washington DC, USA: IEEE, 2013. 2442-2447 http://ieeexplore.ieee.org/document/6580200 [23] 方标, 黄高明, 高俊. LFM宽带雷达信号的多通道盲压缩感知模型研究.自动化学报, 2015, 41(3):591-600 http://www.aas.net.cn/CN/abstract/abstract18636.shtmlFang Biao, Huang Gao-Ming, Gao Jun. A multichannel blind compressed sensing framework for linear frequency modulated wideband radar signals. Acta Automatica Sinica, 2015, 41(3):591-600 http://www.aas.net.cn/CN/abstract/abstract18636.shtml [24] 伍飞云, 周跃海, 童峰.基于似零范数和混合优化的压缩感知信号快速重构算法.自动化学报, 2014, 40(10):2145-2150 http://www.aas.net.cn/CN/abstract/abstract18489.shtmlWu Fei-Yun, Zhou Yue-Hai, Tong Feng. A fast sparse signal recovery algorithm based on approximate l0 norm and hybrid optimization. Acta Automatica Sinica, 2014, 40(10):2145-2150 http://www.aas.net.cn/CN/abstract/abstract18489.shtml [25] 林可祥, 汪一飞.伪随机码的原理与应用.北京:人民邮电出版社, 1978. 135-162Lin Ke-Xiang, Wang Yi-Fei. The Principle and Application of Pseudorandom Code. Beijing:Posts and Telecommunications Press, 1978. 135-162 [26] Bernieri A, Ferrigno L, Laracca M, Landi C. Efficiency of active electrical power consumption in the presence of harmonic pollution: a sensitive analysis. In: Proceedings of the 2010 Instrumentation and Measurement Technology Conference. Austin, Texas, USA: IEEE, 2010. 1447-1452 http://ieeexplore.ieee.org/document/5487994/ [27] 郑建中, 陆祖良, 李敏.电能表动态特性实验研究.电测与仪表, 2011, 48(3):1-7 http://mall.cnki.net/magazine/Article/DCYQ201103005.htmZheng Jian-Zhong, Lu Zu-Liang, Li Min. Experimental research for dynamic characteristic of electrical energy meter. Electrical Measurement and Instrumentation, 2011, 48(3):1-7 http://mall.cnki.net/magazine/Article/DCYQ201103005.htm