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.

Full Text:

PDF


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

Refbacks

  • There are currently no refbacks.


SINERGI
Fakultas Teknik Universitas Mercu Buana
Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650
Tlp./Fax: +62215871335
p-ISSN: 1410-2331
e-ISSN: 2460-1217
http://publikasi.mercubuana.ac.id/index.php/sinergi

 

Creative Commons License
Journal by SINERGI is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View My Stats

 

The Journal is Indexed and Journal List Title by: