@inproceedings{e1251acb8e17455f8e7efac14d4cbcbe,
title = "Harmonic Analysis in Distribution Systems Using a Multi-Step Prediction with NARX",
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.",
keywords = "Distribution system, feed-forward propagation neural network, harmonic distortion, NARX, neural networks",
author = "Raseel Aljendy and Sultan, {Hamdy M.} and Al-Sumaiti, {Ameena Saad} and Diab, {Ahmed A.Zaki}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 ; Conference date: 19-10-2020 Through 21-10-2020",
year = "2020",
month = oct,
day = "18",
doi = "10.1109/IECON43393.2020.9254662",
language = "British English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE Computer Society",
pages = "2545--2550",
booktitle = "Proceedings - IECON 2020",
address = "United States",
}