Electromagnetic time reversal similarity characteristics and its application to locating faults in power networks

Zhaoyang Wang, Reza Razzaghi, Mario Paolone, Farhad Rachidi

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

The existing Electromagnetic Time Reversal (EMTR)-based fault location methods generally leverage the features (e.g., energy) of the signals simulated in the EMTR reversed-time stage (relative to the direct-time stage wherein a fault occurs and its originated transient signals are measured). This paper presents for the first time an integrated time-frequency analysis that identifies the similarity between the signals respectively present in the direct time and in the reversed time. It is demonstrated that the fault current observed at the true fault location exclusively behaves as a quasi-scaled copy of the time-reversed back-injected transient current, such that, the fault location can be identified through a similarity assessment. In this respect, the paper proposes calculating a cross-correlation metric to quantitatively represent the level of similarity between the back-injected transient signal and the fault current signal simulated at the guessed fault locations. The similarity characteristic and the fault location performance of the proposed cross-correlation metric are validated first through simulation case studies based on the IEEE 34-bus test distribution feeder, and then using a pilot test wherein a live medium-voltage radial distribution network was subject to realistic fault occurrences. It is demonstrated that the proposed similarity metric is applicable to locating various types of faults and is robust against uncertainties like fault impedance and fault inception angle.

Original languageEnglish
Pages (from-to)1735-1748
Number of pages14
JournalIEEE Transactions on Power Delivery
Volume35
Issue number4
DOIs
Publication statusPublished - 2020

Keywords

  • Cross-correlation
  • electromagnetic time reversal
  • fault location
  • similarity

Cite this