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

Widi Aribowo

Abstract


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.


Keywords


Power System Stabilizer (PSS); DTDNN; Recurrent Neural Network; Single machine.

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DOI: http://dx.doi.org/10.22441/sinergi.2018.3.009

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SINERGI
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Fakultas Teknik Universitas Mercu Buana
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p-ISSN: 1410-2331
e-ISSN: 2460-1217
Journal URL: http://publikasi.mercubuana.ac.id/index.php/sinergi
Journal DOI: 10.22441/sinergi

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