Title :
Neural network control for damping of multi-mode oscillations in a power system
Abstract :
A neural network-based control scheme, in conjunction with a coherency recognition technique, is proposed for enhancing the damping characteristics of multi-machine power systems. From the simulation results obtained, it is shown that the proposed control scheme is suitable for damping multi-mode oscillations in a 10-machine power system and performs better than a conventional control scheme
Keywords :
circuit oscillations; control system analysis; control system synthesis; damping; decentralised control; neurocontrollers; power system control; power system stability; coherency recognition technique; control design; control simulation; damping characteristics enhancement; decentralised control; multi-machine power systems; neural network control; neurocontrollers; power system multi-mode oscillations damping; Control systems; Damping; Intelligent networks; Neural networks; Optimal control; Power system control; Power system dynamics; Power system simulation; Power systems; Signal generators;
Conference_Titel :
TENCON 2001. Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology
Print_ISBN :
0-7803-7101-1
DOI :
10.1109/TENCON.2001.949675
