Control of advanced static VAr generator by using recurrent neural networks

Author

Chen, Wei ; Liu, Yongqiang ; Chen, Jun ; Wu, Jie

Author_Institution

Electr. Power Coll., South China Univ. of Technol., Guangzhou, China

Volume

2

fYear

1998

fDate

18-21 Aug 1998

Firstpage

839

Abstract

According to the dynamic characteristic of the advanced static VAr generator (ASVG), a recurrent neural network (RNN) based inverse dynamic controller is constructed in this paper, and its training algorithm is given. Taking the single machine infinite bus power system, a three-phase short circuit is used for the test of the proposed RNN controller. Simulation results show the RNN controller can learn the inverse dynamic of a controlled power system and has better performance than the PID controller

Keywords

neurocontrollers; power system control; recurrent neural nets; static VAr compensators; advanced static VAr generator control; inverse dynamic controller; recurrent neural networks; single machine infinite bus power system; three-phase short circuit; training algorithm; Character generation; Circuit simulation; Circuit testing; Control system synthesis; Control systems; Power system dynamics; Power system simulation; Reactive power; Recurrent neural networks; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4754-4

Type

conf

DOI

10.1109/ICPST.1998.729203

Filename

729203