Abstract
The increasing complexity of modern power systems highlights the need for advanced modelling techniques for effective control of power systems. This paper presents results of simulation and practical studies carried out on identifying the dynamics of a single turbogenerator connected to an infinite bus through a short transmission line, using a continually online trained (COT) artificial neural network (ANN).
Recommended Citation
G. K. Venayagamoorthy and R. G. Harley, "A Continually Online Trained Artificial Neural Network Identifier for a Turbogenerator," Proceedings of the International Conference on Electric Machines and Drives, 1999. IEMD '99, Institute of Electrical and Electronics Engineers (IEEE), Jan 1999.
The definitive version is available at https://doi.org/10.1109/IEMDC.1999.769128
Meeting Name
International Conference on Electric Machines and Drives, 1999. IEMD '99
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Computer Simulation; Continually Online Trained Artificial Neural Network Identifier; Control Simulation; Control System Analysis; Dynamics Identification; Learning (Artificial Intelligence); Machine Control; Machine Theory; Modelling Techniques; Neurocontrollers; Parameter Estimation; Power Systems; Short Transmission Line; Turbogenerator Control; Turbogenerators
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1999 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1999
