Experimental Studies with Continually Online Trained Artificial Neural Network Identifiers for Multiple Turbogenerators on the Electric Power Grid
This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1614
There were 3 downloads as of 28 Jun 2016.
Abstract
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
