Assessment of moisture content in power transformer based on traditional techniques and Adaptive neuro-fuzzy interference system

Permit Sekatane, Johan Jordaan, Pitshou Bokoro

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

5 Citations (Scopus)

Abstract

The use of traditional measurement techniques for condition monitoring of power transformer is still a common practice in the power industry. These techniques have proven to be unreliable as a result of sampling and analysis errors. Given the unequal moisture distribution between cellulose and mineral oil in power transformers, the dryness correlation between the two liquid insulators is not always accurate. The aim of this work is to advice the manufacturer of power transformers to continue use the Dew point measurement or move to the modern methods, like frequency domain spectroscopy (FDS). Dew point measurements have been used to estimate the dryness of power transformers, model the data by adaptive neuro-fuzzy inference system (ANFIS) as is proven to solve complex data and validate the results by Frequency Domain spectroscopy (FDS).

Original languageEnglish
Title of host publicationELECO 2019 - 11th International Conference on Electrical and Electronics Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages987-991
Number of pages5
ISBN (Electronic)9786050112757
DOIs
Publication statusPublished - Nov 2019
Event11th International Conference on Electrical and Electronics Engineering, ELECO 2019 - Bursa, Turkey
Duration: 28 Nov 201930 Nov 2019

Publication series

NameELECO 2019 - 11th International Conference on Electrical and Electronics Engineering

Conference

Conference11th International Conference on Electrical and Electronics Engineering, ELECO 2019
Country/TerritoryTurkey
CityBursa
Period28/11/1930/11/19

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

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