scholarly journals NEURAL NETWORK PREDICTIVE CONTROL BASED POWER SYSTEM STABILIZER

2011 ◽  
Vol 39 (6) ◽  
pp. 1431-1447
Author(s):  
Ali Yousef
2003 ◽  
Vol 16 (5-6) ◽  
pp. 891-898 ◽  
Author(s):  
Wenxin Liu ◽  
Ganesh K. Venayagamoorthy ◽  
Donald C. Wunsch

SINERGI ◽  
2018 ◽  
Vol 22 (3) ◽  
pp. 205
Author(s):  
Widi Aribowo

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.


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