Title :
Transient stability assessment using artificial neural networks
Author :
Krishna, S. ; Padiyar, K.R.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India
Abstract :
Online transient stability assessment (TSA) of a power system is not yet feasible due to the intensive computation involved. Artificial neural networks (ANN) have been proposed as one of the approaches to this problem because of their ability to quickly map nonlinear relationships between the input data and the output. In this paper a review of the previously published papers on TSA using ANN is presented. The paper also reports the results of the application of ANN to the problem of TSA of a 10 machine 39 bus system.
Keywords :
neural nets; power system analysis computing; power system transient stability; 10 machine 39 bus system; artificial neural networks; nonlinear relationships mapping; transient stability assessment; Artificial neural networks; Data security; Input variables; Nonlinear dynamical systems; Power system dynamics; Power system security; Power system simulation; Power system stability; Power system transients; Testing;
Conference_Titel :
Industrial Technology 2000. Proceedings of IEEE International Conference on
Print_ISBN :
0-7803-5812-0
DOI :
10.1109/ICIT.2000.854241
