DocumentCode :
2440968
Title :
Application of neural networks to power system security: technology and trends
Author :
Fischl, R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
Volume :
6
fYear :
1994
fDate :
27 Jun- 2 Jul 1994
Firstpage :
3719
Abstract :
This paper presents an overview of the application of artificial neural networks (NN) to power system security assessment. It is noted that although the majority of NN architectures used is the multilayered perceptron, some work has been done to use the Hopfield and the Kohonen networks. In either case, the present applications are illustrated using small power systems, and the key issues are the selection of the input data, training set and the evaluation of the NN design in terms of its accuracy in predicting the security of the power system. Most of the discussion in this paper is concerned with the latter issue since it has not been addressed extensively in the literature
Keywords :
neural nets; power system analysis computing; power system security; Hopfield neural net; Kohonen neural networks; input data; multilayered perceptron; neural networks; power system security assessment; training set; Application software; Artificial neural networks; Computer networks; Data security; Neural networks; Neurons; Performance analysis; Power system analysis computing; Power system security; Power systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
Type :
conf
DOI :
10.1109/ICNN.1994.374801
Filename :
374801
Link To Document :
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