A dimension reduction method used in detecting errors of distribution transformer connectivity

Zeyang Tang*, Yu Shen, Kunpeng Zhou, Kan Cao, Fan Yang, Defu Cai, Chengke Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Many power utilities may have problems with the quality of data in records about which feeder a distribution transformer is connected to. This affects the operation and maintenance of smart grid infrastructure, outage management, line loss management, and workforce safety. The traditional manual way of verifying and updating the distribution transformer connectivity (DTC) is time-consuming and labor-intensive. Researchers have proposed the method which makes use of secondary side single-phase voltage of distribution transformers to verify DTC. However, when the windings of distribution transformers are yyn0 connected, the performance of the single-phase voltage method (SPVM) is unsatisfactory due to the unbalanced three-phase voltages. This paper proposed a dimension reduction method (DRM) that can convert the unbalanced three-phase voltage to a balanced voltage. The data which include 29 days' secondary side voltages of 3866 distribution transformers have been collected. The performances of the DRM and the SPVM have been compared. Results show that the DRM always has higher accuracy compared with SPVM. The influences of the maximum voltage difference and the reference distribution transformer have also been discussed. The DRM's results are more stable compared with SPVM.
Original languageEnglish
Pages (from-to)79408-79418
Number of pages11
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 27 Apr 2020

Keywords

  • distribution transformer connectivity
  • data-driven
  • dimension reduction method
  • similarity
  • unbalanced

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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