The increasing complexity of a modern power grid highlights the need for advanced system identification techniques for effective control of power systems. This paper provides a new method for nonlinear identification of turbogenerators in a 3-machine 6-bus power system using online trained feedforward neural networks. Each turbogenerator in the power system is equipped with a neuro-identifier, which is able to identify its particular turbogenerator and the rest of the network to which it is connected from moment to moment, based on only local measurements. Each neuro-identifier can then be used in the design of a nonlinear neurocontroller for each turbogenerator in such a multi-machine power system. Experimental results for the neuro-identifiers are presented to prove the validity of the concept
G. K. Venayagamoorthy et al., "Experimental Studies with Continually Online Trained Artificial Neural Network Identifiers for Multiple Turbogenerators on the Electric 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.2001.939543
International Joint Conference on Neural Networks, 2001. IJCNN '01
Electrical and Computer Engineering
Keywords and Phrases
Electric Power Grid; Feedforward Neural Nets; Feedforward Neural Networks; Identification; Learning (Artificial Intelligence); Multiple Machine Power System; Neural Network; Neurocontrollers; Online Learning; Power System Identification; Real-Time Systems; Turbogenerators
Article - Conference proceedings
© 2001 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.