Experimental verification of a generating unit excitation neuro-controller

Author

Salem, M.M. ; Zaki, A.M. ; Mahgoub, O.A. ; El-Zahab, E. Abu ; Malik, O.P.

Author_Institution

Electron. Res. Inst., Cairo, Egypt

Volume

1

fYear

2000

fDate

2000

Firstpage

585

Abstract

A feedforward neural network (FFNN) based excitation neuro-controller (ENC), which integrates the functions of both the AVR and the PSS, has been implemented and experimentally verified on-line on a physical model of a single-machine infinite-bus power system. The FFNN has a simple structure and needs only the terminal voltage and generator speed to be measured. The ENC output signal depends on the on-line training and a modified error function used in training. The performance of the proposed ENC has been investigated by a number of experimental tests for a variety of operating conditions and disturbances

Keywords

feedforward neural nets; neurocontrollers; power generation control; power system control; power system stability; synchronous generators; voltage control; AVR; PSS; automatic voltage regulator; feedforward neural network; generating unit excitation neuro-controller; generator speed; modified error function; on-line training; output signal; power system stabiliser; single-machine infinite-bus power system; synchronous generator; terminal voltage; Digital signal processing; Digital signal processing chips; Error correction; Iterative algorithms; Neurofeedback; Neurons; Output feedback; Power system modeling; Signal processing algorithms; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society Winter Meeting, 2000. IEEE

Print_ISBN

0-7803-5935-6

Type

conf

DOI

10.1109/PESW.2000.850067

Filename

850067