• HOME
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • Chinese
Site search        
文章摘要
基于超状态隐马尔可夫模型的智能电能表非侵入式故障远程检定
Non-intrusive remote error detection and localization for smart meters based on super-state hidden Markov model
Received:November 01, 2020  Revised:November 11, 2020
DOI:10.19753/j.issn1001-1390.2023.02.028
中文关键词: 智能电能表  超状态隐马尔可夫模型  故障检测  概率模型
英文关键词: smart meter, super-state hidden Markov model, fault detection, probabilistic model
基金项目:国家电网公司科技项目(520626200053)
Author NameAffiliationE-mail
Jing Zhen* State Grid Shandong Electric Power Company jz_sddky@outlook.com 
Wang Li State Grid Shandong Electric Power Company jz_sddky@outlook.com 
Yang Mei Shandong Institute of Metrology jz_sddky@outlook.com 
Wang Zhelong State Grid Shandong Electric Power Company jz_sddky@outlook.com 
Wang Xiaoyong State Grid Shandong Electric Power Company jz_sddky@outlook.com 
Hits: 1581
Download times: 338
中文摘要:
      存在故障或误差的智能电能表不仅给电网企业带来经济损失,而且其中的安全隐患容易影响电网的稳定运行,尤其是对成分复杂的智能电网体系。针对这一问题,提出一种基于超状态隐马尔可夫模型(Super-State Hidden Markov Model,SSHMM)对故障电能表进行非侵入式远程检测与定位。该方法不仅能发现已经出现故障的电能表,还可以对最有可能出现故障的电能表进行估计,为电网企业的运营管理提供参考,在真实数据集上的实验结果验证了该方法的有效性与稳定性。
英文摘要:
      Smart meters with faults or errors can cause economic losses to power grid companies, and the hidden safety hazards can also easily affect the stable operation of the power grid, especially for smart grid systems with complex components. Aiming at this problem, non-intrusive remote detection and location of faulted electricity meters based on a super-state hidden Markov model (SSHMM) is proposed in this paper. This method can not only find the meter which has failed but also estimate the meter which is most likely to fail and provide a reference for the operation and management of the power grid enterprises. Experimental results on real data sets verify the efficiency and stability of the proposed method.
View Full Text   View/Add Comment  Download reader
Close
  • Home
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • 中文页面
Address: No.2000, Chuangxin Road, Songbei District, Harbin, China    Zip code: 150028
E-mail: dcyb@vip.163.com    Telephone: 0451-86611021
© 2012 Electrical Measurement & Instrumentation
黑ICP备11006624号-1
Support:Beijing Qinyun Technology Development Co., Ltd