Title :
A continually online trained artificial neural network identifier for a turbogenerator
Author :
Venayagamoorthy, Ganesh K. ; Harley, Ronald G.
Author_Institution :
Dept. of Electr. Eng., Natal Univ., Durban, South Africa
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)
Keywords :
control system analysis; learning (artificial intelligence); machine control; machine theory; neurocontrollers; parameter estimation; turbogenerators; computer simulation; continually online trained artificial neural network identifier; control simulation; dynamics identification; modelling techniques; power systems; short transmission line; turbogenerator control; Artificial neural networks; Mathematical model; Power system control; Power system dynamics; Power system modeling; Power system simulation; Transmission lines; Turbines; Turbogenerators; Voltage;
Conference_Titel :
Electric Machines and Drives, 1999. International Conference IEMD '99
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-5293-9
DOI :
10.1109/IEMDC.1999.769128
