Harmonic Analysis in Distribution Systems Using a Multi-Step Prediction with NARX

Raseel Aljendy, Hamdy M. Sultan, Ameena Saad Al-Sumaiti, Ahmed A.Zaki Diab

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

4 Scopus citations

Abstract

This paper proposes a multi-step prediction method for the total harmonic distortion (THD) in three-phase networks with nonlinear loads using a nonlinear autoregressive network with exogenous inputs (NARX).The prediction is performed in three stages: in an open-loop neural network, closed-loop mode, and open-loop mode with the removal of the delay time. To verify the accuracy of the proposed method for identifying the harmonic source, comparisons are performed with two types of neural networks, a feed-forward back-propagation (FFBP) neural network and a cascaded feed-forward back-propagation (CFFBP) neural network. Moreover, three different cases of nonlinear loads are studied to validate the effectiveness of the proposed technique for harmonic prediction. A MATLAB/Simulink program is used for the modelling and simulation of the distribution system and all neural networks.

Original languageBritish English
Title of host publicationProceedings - IECON 2020
Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages2545-2550
Number of pages6
ISBN (Electronic)9781728154145
DOIs
StatePublished - 18 Oct 2020
Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
Duration: 19 Oct 202021 Oct 2020

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2020-October

Conference

Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Country/TerritorySingapore
CityVirtual, Singapore
Period19/10/2021/10/20

Keywords

  • Distribution system
  • feed-forward propagation neural network
  • harmonic distortion
  • NARX
  • neural networks

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