An adaptive neural network identifier for effective control of a static compensator connected to a power system

Author

Mohagheghi, Salman ; Park, Jung-Wook ; Harley, Ronald G. ; Venayagamoorthy, Ganesh K. ; Crow, Mariesa L.

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

4

fYear

2003

fDate

20-24 July 2003

Firstpage

2964

Abstract

A novel method for nonlinear identification of a static compensator connected to a power system using continually online trained (COT) artificial neural networks (ANNs) is presented in this paper. The identifier is successfully trained online to track the dynamics of the power network without any need for offline data and can be used in designing an adaptive neurocontroller for a static compensator connected to such system.

Keywords

identification; neurocontrollers; power system control; static VAr compensators; adaptive neural network identifier; adaptive neurocontroller; continually online trained artificial neural networks; power electronic based shunt connected flexible AC transmission system devices; power system; static compensator; Adaptive control; Adaptive systems; Artificial neural networks; Control systems; Neural networks; Power system control; Power system dynamics; Power systems; Programmable control; STATCOM;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2003. Proceedings of the International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-7898-9

Type

conf

DOI

10.1109/IJCNN.2003.1224042

Filename

1224042