Discussion of "A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system" [and reply]

2000 ◽  
Vol 15 (4) ◽  
pp. 494 ◽  
Author(s):  
S.N. Singh ◽  
K.N. Srivastava ◽  
B. Changaroon ◽  
S. Chandra Srivastava ◽  
D. Thukaram
Keyword(s):  
Neural Network ◽  
Power System ◽  
Power System Stabilizer ◽  
Practical Case ◽  
On Line ◽  
System Stabilizer

Design of an adaptive neural network based power system stabilizer

2003 ◽  
Vol 16 (5-6) ◽  
pp. 891-898 ◽  
Author(s):  
Wenxin Liu ◽  
Ganesh K. Venayagamoorthy ◽  
Donald C. Wunsch
Keyword(s):  
Neural Network ◽  
Power System ◽  
Power System Stabilizer ◽  
Adaptive Neural Network ◽  
System Stabilizer

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

SINERGI ◽  
2018 ◽  
Vol 22 (3) ◽  
pp. 205
Author(s):  
Widi Aribowo
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Power System ◽  
Delay Line ◽  
Power System Stability ◽  
System Stability ◽  
Power System Stabilizer ◽  
Robust Performance ◽  
Distributed Time Delay ◽  
System Stabilizer

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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