Abstract
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbances
Recommended Citation
G. K. Venayagamoorthy et al., "Excitation and Turbine Neurocontrol with Derivative Adaptive Critics of Multiple Generators on the Power Grid," Proceedings of the International Joint Conference on Neural Networks, 2001. IJCNN '01, Institute of Electrical and Electronics Engineers (IEEE), Jan 2001.
The definitive version is available at https://doi.org/10.1109/IJCNN.2001.939494
Meeting Name
International Joint Conference on Neural Networks, 2001. IJCNN '01
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Derivative Adaptive Critics; Dynamics; Excitation; Heuristics; Learning (Artificial Intelligence); Learning Algorithm; Neurocontrollers; Optimisation; Power System Control; Power System Stability; Stability; Three-Machine Power System; Turbine Generator
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2001 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2001
