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An artificial neural network based method for harmonic detection in power system

  • Harbin Institute of Technology

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

Abstract

A novel advanced harmonic detection method based on neural network (NN) is proposed in this paper. It is an adaptive harmonic detection method with variable step-size based on adaptive linear NN and self-adaptive noise countervailing principle. And this proposed method adopts a sliding integrator to extract the real tracing error and then uses a fuzzy adjuster with self-adjustable factor to modify the step-size. So the novel harmonic detection method can obtain fast convergence speed and high steady-state precision at the same time. Comparisons are made between conventional harmonic detection methods based on NN and the advanced method based on NN proposed in this paper. Finally detailed simulation and experimental results verify the validity and superiority of the advanced methods.

Original languageEnglish
Title of host publication2008 23rd Annual IEEE Applied Power Electronics Conference and Exposition, APEC
Pages456-461
Number of pages6
DOIs
StatePublished - 2008
Event2008 23rd Annual IEEE Applied Power Electronics Conference and Exposition, APEC - Austin, TX, United States
Duration: 24 Feb 200828 Feb 2008

Publication series

NameConference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC

Conference

Conference2008 23rd Annual IEEE Applied Power Electronics Conference and Exposition, APEC
Country/TerritoryUnited States
CityAustin, TX
Period24/02/0828/02/08

Keywords

  • Fuzzy adjuster
  • Harmonic detection
  • Neural network (NIN)
  • Self-adaptive noise countervailing principle

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