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
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