Online learning recurrent neural network stabilization controller for multi-machine power system

PowerCon 2000 - 2000 International Conference on Power System Technology, Proceedings

Volumn 1, Issue , 2000, Pages 223-228

  Senjyu, Tomonobu ^a   Yoshiteru, Morishima ^a   Uezato, Katsumi ^a  

^a UNIVERSITY OF THE RYUKYUS   (Japan)

Author keywords

Genetic algorithm; Online learning; Recurrent neural network stabilization controller

Indexed keywords

CONTROLLERS; E-LEARNING; ELECTRIC POWER SYSTEMS; GENETIC ALGORITHMS; NONLINEAR CONTROL SYSTEMS; RECURRENT NEURAL NETWORKS; STABILIZATION;

CONTROLLER ROBUSTNESS; DAMPING POWER SYSTEM OSCILLATIONS; MULTI MACHINE POWER SYSTEM; ONLINE LEARNING; ONLINE TUNING; OPERATING CONDITION; STABILITY OF POWER SYSTEM; STABILIZATION CONTROLLERS;

ELECTRIC POWER SYSTEM CONTROL;

EID: 42549147200     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPST.2000.900060     Document Type: Conference Paper

References (4)

1. T. Senjyu, A. Miyazato, K. Uezato, and H. K. Hee, "Improvement of Multi-Machine Power System Stability by cooperative Control of AVR and GOV Using FuzzyGenetic Controller", Intelligent System Application Power Systems, July 6-10, pp. 89-93, 1997.
2. Teturo Yabuta, Takayuki Yamada, "Neural Network Controller Characteristics with Regard to Adaptive Control", IEEE Trans. Power Systems, Vo. 22, No. 1, pp. 170-176, 1992.
3. Y.-Y. Hsu, and L. H. Jeng, "Damping of subsynchronous oscillations using adaptive controllers tuned by artificial neutral networks", IEE Pro.-Gener. Transm. Distrib, Vol. 142, No. 4, pp. 415-422, 1995.
4. Srinivas Pillutla and Ali Keyhani, "Power system stabilization based on modular neural network architecture", Electrical & Energy Systems, Vol. 19, No. 6, pp. 411-418, 1997.