文章摘要
杜蜀薇,彭楚宁,徐石明,等.基于贝叶斯层次模型的电能表检定装置在线核查方法[J].电力系统自动化,2018,42(18):177-181. DOI: 10.7500/AEPS20180118001.
DU Shuwei,PENG Chuning,XU Shiming, et al.Online Verification Method of Meter Calibration Equipment Based on Hierarchical Bayes Model[J].Automation of Electric Power Systems,2018,42(18):177-181. DOI: 10.7500/AEPS20180118001.
基于贝叶斯层次模型的电能表检定装置在线核查方法
Online Verification Method of Meter Calibration Equipment Based on Hierarchical Bayes Model
DOI:10.7500/AEPS20180118001
关键词: 虚拟标准电能表  智能电能表检定装置  在线核查  期间核查  中心极限定理  贝叶斯层次模型
KeyWords: virtual standard meter  smart meter calibration equipment  online verification  period verification  central limit theorem  hierarchical Bayes model
上网日期:2018-08-07
基金项目:
作者单位E-mail
杜蜀薇 国家电网有限公司, 北京市 100031  
彭楚宁 国家电网有限公司, 北京市 100031  
徐石明 南瑞集团(国网电力科学研究院)有限公司, 江苏省南京市 211106  
李天阳 南瑞集团(国网电力科学研究院)有限公司, 江苏省南京市 211106 litianyang@sgepri.sgcc.com.cn 
摘要:
      针对智能电能表检定装置期间核查导致检定工作中断,核查频度不易提高难以及时发现智能电能表检定装置准确度失效的现状,提出了一种电能表检定装置在线核查新方法。利用同一批次智能电能表实时检定数据,基于中心极限定理和贝叶斯层次模型,构建了高准确度等级的虚拟标准电能表。通过虚拟标准电能表在线核查智能电能表检定装置的测量误差,实现了检定工作状态下对检定装置性能的核查。仿真测试比对及真实数据验证结果表明,该方法在不影响检定工作的前提下,能以较高频度开展智能电能表检定装置核查工作,证实了该方法在大规模自动化检定模式下的优越性。
Abstract:
      The period verification procedures of smart meter calibration equipment require the suspension of the routine detection process, and it is difficult to increase the verification frequency and difficult to timely uncover the inaccuracy of smart meter calibration equipment. To solve this problem, this paper proposes a new online verification method of smart meter calibration equipment. Based on central limit theorem and Bayes hierarchical model, this method utilizes real-time detection data of same-batch smart meters and constructs a high-accuracy virtual standard meter. Through this virtual standard meter, the measurement error of the calibration equipment is verified online and the verification of smart meter calibration equipment under the detection process of smart meters is accomplished. In addition, the results of simulation tests and field experiments show frequent verification tasks can be accomplished without affecting the routine calibration process, thus demonstrates the superiority of this method under large-scale automatic detection mode.
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