Online Identificaiton of Turbogenerators in a Multimachine Power System using Radial Basis Function Neural Networks
Abstract
The electric power system is a complex nonlinear time varying system that needs advanced intelligent techniques for online system identification and modeling in order to control the turbogenerators in a more efficient and fast manner. This paper shows the use radial basis function neural networks (RBFNNS) to carry out online identification of turbogenerators in an multimachine power system. Simulation results show that two separate RBFNNs can be used to identify the speed and terminal voltage deviations of the turbogenerators when subjected to changes in operating points and conditions.
Recommended Citation
S. Singh and G. K. Venayagamoorthy, "Online Identificaiton of Turbogenerators in a Multimachine Power System using Radial Basis Function Neural Networks," Intelligent Engineering Systems Through Artificial Neural Networks, American Society of Mechanical Engineers (ASME), Nov 2002.
Meeting Name
Artificial Neural Networks in Engineering Conference, ANNIE 2002 (2002: Nov. 10-13, St. Louis, MO)
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Electric Power System; Multimachine Power System; Turbogenerators
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2002 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
13 Nov 2002
