On-line monitoring of metal-oxide surge arresters using improved equivalent model with evolutionary optimisation algorithm

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

14 Citations (Scopus)

Abstract

A resistive-current extraction algorithm to assist with on-line monitoring of surge arresters is proposed in this paper. The algorithm is based on the improved equivalent model for surge arresters and combines evolutionary optimisation with the base-frequency approximating method. A genetic algorithm is used to obtain the optimal capacitance such that the phase shift between the base-components of the branch voltage and current is minimised thereby yielding a good approximation of the resistive current. In this paper, the algorithm is implemented and tested using Matlab/Simulink. Results indicate that the proposed algorithm is able to efficiently and accurately obtain the resistive component of the leakage current, using the improved equivalent model, under both ideal and distorted supply conditions.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages135-139
Number of pages5
ISBN (Electronic)9781509014125
DOIs
Publication statusPublished - 3 Aug 2017
Event26th IEEE International Symposium on Industrial Electronics, ISIE 2017 - Edinburgh, Scotland, United Kingdom
Duration: 18 Jun 201721 Jun 2017

Publication series

NameIEEE International Symposium on Industrial Electronics

Conference

Conference26th IEEE International Symposium on Industrial Electronics, ISIE 2017
Country/TerritoryUnited Kingdom
CityEdinburgh, Scotland
Period18/06/1721/06/17

Keywords

  • Evolutionary optimisation
  • Genetic algorithm
  • Resistive current extraction
  • Surge arresters

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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