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

Widi Aribowo

doi:10.22441/sinergi.2018.3.009

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

Authors

Widi Aribowo Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Indonesia

DOI:

https://doi.org/10.22441/sinergi.2018.3.009

Keywords:

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

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.