Excitation and turbine neurocontrol with derivative adaptive critics of multiple generators on the power grid

Author

Venayagamoorthy, Ganesh K. ; Harley, R.G. ; Wunsch, D.C.

Author_Institution

Dept. of Electron. Eng., ML Sultan Tech., Durban, South Africa

Volume

2

fYear

2001

fDate

2001

Firstpage

984

Abstract

Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbances

Keywords

dynamics; learning (artificial intelligence); neurocontrollers; optimisation; power system control; power system stability; derivative adaptive critics; dynamics; excitation; heuristics; learning algorithm; neurocontrollers; power system control; stability; three-machine power system; turbine generator; Adaptive control; Automatic generation control; Electric variables control; Mesh generation; Neurocontrollers; Power system dynamics; Power system simulation; Power system stability; Programmable control; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.939494

Filename

939494