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提高智能电能表可靠性技术研究综述
引用本文:马永超,赵伟,黄松岭. 提高智能电能表可靠性技术研究综述[J]. 电测与仪表, 2022, 59(4): 1-7. DOI: 10.19753/j.issn1001-1390.2022.04.001
作者姓名:马永超  赵伟  黄松岭
作者单位:清华大学电机工程与应用电子技术系,北京100084
基金项目:国家自然科学基金资助项目(52077112);
摘    要:智能电能表在电网中的作用越来越重要,但其在使用过程中常发生故障,且故障类型多样,因此如何提高其可靠性逐渐受到重视.文章基于智能电能表的一般架构及其功能,从固有可靠性和使用可靠性两方面,对现有旨在提高智能电能表可靠性的技术进行了梳理.固有可靠性技术涵盖智能电能表的结构设计、硬件可靠性分析、关键模块研制以及软件测试等.而使...

关 键 词:智能电能表  固有可靠性  使用可靠性  软件测试  人工智能技术  大数据
收稿时间:2020-07-03
修稿时间:2020-07-03

Techniques for improving the robustnessof smart meters: A review
Ma Yongchao,Zhao Wei and Huang Songling. Techniques for improving the robustnessof smart meters: A review[J]. Electrical Measurement & Instrumentation, 2022, 59(4): 1-7. DOI: 10.19753/j.issn1001-1390.2022.04.001
Authors:Ma Yongchao  Zhao Wei  Huang Songling
Affiliation:Department of Electric Engineering,Tsinghua University,Department of Electric Engineering,Tsinghua University,Department of Electric Engineering,Tsinghua University
Abstract:The smart meter plays an increasingly important role in power grids. However, operation failures, caused by different faults during power metering, are often observed. Therefore, improving the robustness of smart meters becomes important and has been focused by many studies. In this paper, based on an introduction of the general structure and function of a smart meter, we summarize different techniques for improving the smart meter robustness into two categories, i.e. the inherent reliability and the use reliability respectively. The inherent reliability includes the structure design, hardware reliability analysis, key module development, software testing and so on. While the use reliability focuses on measurement error compensation and operating status detection for smart meters. The latter category involves evaluation systems based on artificial intelligence technologies, such as the full life cycle theory, neural networks, Bayesian algorithm, K-means algorithm, etc. Future development trends towards a more robust smart meter are discussed.
Keywords:smart  meter, inherent  reliability, use  reliability, software  testing, artificial  intelligence technology, big  data
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