TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK

TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK

In this paper, a Distributed Time-Delay Neural Network (DTDNN) algorithm is used to control the Power System Stabilizer (PSS) parameters to find the reliable conditions. The proposed DTDNN algorithm apply tapped delay line memory to set the PSS. In this study, DTDNN consists of a DTDNN-identifier an...

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Main Author: Widi Aribowo
Format: Article
Language:Indonesian
Published: Universitas Mercu Buana 2018-10-01
Series:Jurnal Ilmiah SINERGI
Subjects:
Power System Stabilizer (PSS)
DTDNN
Recurrent Neural Network
Single machine.
Online Access:http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/2668
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spelling doaj-e21e4ac8369d454aa93fcc3f2cc706cb2020-11-24T21:47:45ZindUniversitas Mercu BuanaJurnal Ilmiah SINERGI1410-23312460-12172018-10-0122320521010.22441/sinergi.2018.3.0092256TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORKWidi Aribowo0Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri SurabayaIn this paper, a Distributed Time-Delay Neural Network (DTDNN) algorithm is used to control the Power System Stabilizer (PSS) parameters to find the reliable conditions. The proposed DTDNN algorithm apply tapped delay line memory to set the PSS. In this study, DTDNN consists of a DTDNN-identifier and a DTDNN-controller. The performance of the system with DTDNN-PSS controller is compared with a Recurrent Neural Network PSS (RNN-PSS) and Conventional PSS (C-PSS). The results show the effectiveness of DTDNN-PSS design, and superior robust performance for enhancement power system stability compared to other with different cases.http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/2668Power System Stabilizer (PSS)DTDNNRecurrent Neural NetworkSingle machine.
collection DOAJ
language Indonesian
format Article
sources DOAJ
author Widi Aribowo
spellingShingle Widi Aribowo
TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
Jurnal Ilmiah SINERGI
Power System Stabilizer (PSS)
DTDNN
Recurrent Neural Network
Single machine.
author_facet Widi Aribowo
author_sort Widi Aribowo
title TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
title_short TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
title_full TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
title_fullStr TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
title_full_unstemmed TUNING FOR POWER SYSTEM STABILIZER USING DISTRIBUTED TIME-DELAY NEURAL NETWORK
title_sort tuning for power system stabilizer using distributed time-delay neural network
publisher Universitas Mercu Buana
series Jurnal Ilmiah SINERGI
issn 1410-2331
2460-1217
publishDate 2018-10-01
description In this paper, a Distributed Time-Delay Neural Network (DTDNN) algorithm is used to control the Power System Stabilizer (PSS) parameters to find the reliable conditions. The proposed DTDNN algorithm apply tapped delay line memory to set the PSS. In this study, DTDNN consists of a DTDNN-identifier and a DTDNN-controller. The performance of the system with DTDNN-PSS controller is compared with a Recurrent Neural Network PSS (RNN-PSS) and Conventional PSS (C-PSS). The results show the effectiveness of DTDNN-PSS design, and superior robust performance for enhancement power system stability compared to other with different cases.
topic Power System Stabilizer (PSS)
DTDNN
Recurrent Neural Network
Single machine.
url http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/2668
work_keys_str_mv AT widiaribowo tuningforpowersystemstabilizerusingdistributedtimedelayneuralnetwork
_version_ 1725895855850913792

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