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文章摘要
复杂动态功率信号幅度域特征对电能表动态误差影响
Analysis of amplitude domain characteristics in complex dynamic power signals and their impact on the error of electricity meter
Received:November 22, 2023  Revised:November 24, 2023
DOI:10.19753/j.issn1001-1390.2026.01.020
中文关键词: 复杂动态功率信号  双模态调制模型  幅度域特征  电能表动态误差  敏感特征参量
英文关键词: complex dynamic power signal, bimodal modulation model, amplitude domain feature, dynamic error of electricity meter, sensitive characteristic parameter
基金项目:国家电网有限公司科技项目“高比例新能源接入下宽动态多特征参量电能计量关键技术研究”(5700-202211214A-1-1-ZN)
Author NameAffiliationE-mail
LI Wenwen* Metrology Center, State Grid Jibei Electric Power Company Limited, Beijing 100045, China 821328633@qq.com 
YUAN Ruiming Metrology Center, State Grid Jibei Electric Power Company Limited, Beijing 100045, China ydollars@sina.com 
ZHOU Hui State Grid Corporation of China, Beijing 100031, China zhouhui@sgcc.com.cn 
WANG Guoxing Metrology Center, State Grid Jibei Electric Power Company Limited, Beijing 100045, Chinaited, Beijing 100045, China wang.guoxing@jibei.sgcc.com.cn 
WANG Chen Metrology Center, State Grid Jibei Electric Power Company Limited, Beijing 100045, China wang.chen.d@jibei.sgcc.com.cn 
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中文摘要:
      针对动态负荷电流快速、大范围和随机变化对电能计量影响问题,先建立复杂动态电能信号的非平稳随机过程模型和双模态调制模型,推导出了准稳态项与动态项幅度等模型参量;基于一次样条最小二乘经验模态分解方法,提出了准稳态项与动态项幅度模型参量提取方法,通过电气化铁路牵引变电站和电弧炉功率信号分解案例,证明了方法的正确性;通过准稳态项与动态项幅度域模型参量的映射,构建了复杂动态功率信号的幅度域4个重要特征参量,提取了重要特征;最后,采用电能表动态误差的测试实验方法,证明了文中提出的4个重要特征参量是导致电能表超差的敏感特征参量。
英文摘要:
      Aiming at the influence of the fast, large range and random change of dynamic load current on the electricity metering, this paper firstly establishes a non-stationary random process modulation model and bimodal modulation model for complex dynamic power signal, and derives model parameters such as quasi-steady term and dynamic term amplitude. Based on the first spline least squares empirical mode decomposition (FS-EMD) method, a parameter extraction method for the amplitude model of quasi-steady and dynamic terms is proposed, the correctness of the method is demonstrated through the decomposition of power signals from electrified railway traction substations and arc furnaces. By mapping the amplitude domain model parameters, the important characteristic parameters in amplitude domain representing complex dynamic electric energy signals are constructed, and four important features are extracted. Finally, the dynamic error tests conducted on electricity meters reveal that the four significant parameters identified herein act as critical factors triggering the meter′s performance to exceed tolerance thresholds.
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