Field experience of small quasi-DC bias on power transformers: A first classification of low-frequency current patterns and identification of sources

Dennis Albert*, Philipp Schachinger, Herwig Renner, Peter Hamberger, Franz Klammler, Georg Achleitner

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Low-frequency currents (LFC) or quasi-DC (QDC) in the electrical power transmission network, and especially in power transformers, are causing negative effects such as an increase in noise level, in reactive power consumption and in power losses. Currently, no classification of LFC is available to identify a possible source. In order to identify the origin of undesired LFC, classifications of LFC in current and audio measurements are defined. They are based on a spectrum analysis of current and audio measurements. These classifications are successfully tested in laboratory and field measurements. Consequently, LFC sources are identified by field and laboratory measurements and analytical approaches. For power transformer operators, a user-friendly and fast method is presented to identify LFC in the transformers. The method is based on audible measurements and serves as a first estimator for low-frequency currents in power transformers.

Original languageEnglish
Title of host publicationCigre 2020 Session
Pages427-436
Number of pages10
Volume137
DOIs
Publication statusPublished - Dec 2020
EventCIGRE e-session 2020 - Virtuell, France
Duration: 24 Aug 20203 Sept 2020
https://www.cigre.org/GB/events/cigre-e_session

Publication series

NameElektrotechnik und Informationstechnik
PublisherSpringer Wien
ISSN (Print)0932-383X

Conference

ConferenceCIGRE e-session 2020
Country/TerritoryFrance
CityVirtuell
Period24/08/203/09/20
Internet address

Keywords

  • DC BIas
  • GIC
  • Geomagnetically Induced Currents
  • transformer
  • Transformer Audible Noise
  • Low Frequency Currents
  • Power Transformers
  • quasi-DC
  • transformer neutral point current
  • low-frequency currents
  • transformer noise

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Field experience of small quasi-DC bias on power transformers: A first classification of low-frequency current patterns and identification of sources'. Together they form a unique fingerprint.

Cite this