Improving diagnostic technique of moisture content in power transformers using adaptive neuro-fuzzy inference system

Permit Sekatane, Pitshou Bokoro

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

1 Citation (Scopus)

Abstract

Effective diagnostic techniques of moisture content are fundamentally meant to maximize proper maintenance planning, reliability, quality and safe operation of power transformers. A literature survey reveals that moisture content drastically affects the insulation system of power transformer by; reducing its dielectric strength, accelerating cellulose ageing and causing partial discharge at high temperatures. Traditional technique such as Dew-Point method of moisture evaluation, although used by power transformers' manufacturers, contains few errors related to inaccurate measurements. This work discusses the improvement of Dew-Point (DP) measurement approach using artificial intelligence, particularly the Adaptive Neuro Fuzzy Inference System (ANFIS). The proposed method has proven to have improved the diagnosis efficiency of Dew-Point techniques by 5%.

Original languageEnglish
Title of host publication2021 IEEE PES/IAS PowerAfrica, PowerAfrica 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665403115
DOIs
Publication statusPublished - 23 Aug 2021
Event8th Annual IEEE Power and Energy Society and Industrial Applications Society PowerAfrica Conference, PowerAfrica 2021 - Virtual, Nairobi, Kenya
Duration: 23 Aug 202127 Aug 2021

Publication series

Name2021 IEEE PES/IAS PowerAfrica, PowerAfrica 2021

Conference

Conference8th Annual IEEE Power and Energy Society and Industrial Applications Society PowerAfrica Conference, PowerAfrica 2021
Country/TerritoryKenya
CityVirtual, Nairobi
Period23/08/2127/08/21

Keywords

  • Adaptive neuro-fuzzy inference system
  • Diagnostic technique
  • Moisture content
  • Power transformers

ASJC Scopus subject areas

  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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