JOURNAL ARTICLE

Fault current limiter principle by switching magnetic circuit.

  • Published In: Electrical Engineering in Japan, 2024, v. 217, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Tsukima, Mitsuru; Hatauchi, Yamato 3 of 3

Abstract

Several types of fault current limiters have been studied so far, including superconductor based one or nonsuperconductor based one. However, it is difficult to satisfy all requirements for cost, maintainability, and current limiting performance. This study proposes another type of fault current limiter, variable transformer based one. It is supposed to be less expensive and easier to be maintained since it is based on the conventional transformer, and to be expected better current limiting performance since the magnetic circuit of the transformer is drastically changed. The magnetic circuit of the transformer is switched to be opened and to produce another one by shifting a portion of its iron core mechanically, allowing the primary and secondary electric circuit to be magnetically isolated. In that way, the electromotive force of the secondary winding could be reduced so that the secondary current could be limited. The prototype based on this concept was designed and built up, and its stational performance has been investigated. As a result, it was confirmed that the prototype shows good current limiting performances identical to the results of the previous FE analysis. Furthermore, the prototype was connected to the operating mechanism to investigate the transient performances, and as a result, satisfying current limiting performances are confirmed [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Electrical Engineering in Japan. 2024/03, Vol. 217, Issue 1, p1
  • Document Type:Article
  • Subject Area:Engineering
  • Publication Date:2024
  • ISSN:0424-7760
  • DOI:10.1002/eej.23463
  • Accession Number:175852857
  • Copyright Statement:Copyright of Electrical Engineering in Japan is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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