Levenberg–Marquardt neural network to estimate UPFC-coordinated PSS parameters to enhance power system stability

2017 ◽  
Vol 31 (4) ◽  
pp. 1237-1248 ◽  
Author(s):  
Md Juel Rana ◽  
Mohammad Shoaib Shahriar ◽  
Md Shafiullah
Keyword(s):  
Neural Network ◽  
Power System ◽  
Power System Stability ◽  
System Stability ◽  
Levenberg Marquardt

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.

Improvement of multi-machine power system stability with variable series capacitor using on-line learning neural network

2003 ◽  
Vol 25 (5) ◽  
pp. 403-409 ◽  
Author(s):  
Tomonobu Senjyu ◽  
Shotaro Yamane ◽  
Yoshiteru Morishima ◽  
Katsumi Uezato ◽  
Hideki Fujita
Keyword(s):  
Neural Network ◽  
Power System ◽  
Power System Stability ◽  
System Stability ◽  
On Line ◽  
On Line Learning ◽  
Series Capacitor
Sign in / Sign up

Export Citation Format

Share Document