By Topic

Artificial neural networks applied in study of atmospheric parameters to high voltage substations concerning lightning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
de Souza, A.N. ; Dept. of Electr. Eng., Sao Paulo Univ., Brazil ; da Silva, I.N. ; Bordon, M.E.

This paper demonstrates that artificial neural networks can be used effectively for estimation of parameters related to study of atmospheric conditions in high voltage substation design. Specifically, the neural networks are used to compute the variation of electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric factors, such as pressure, temperature, humidity, so on. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the verification of the influence of atmospheric conditions on design of substations concerning lightning

Published in:

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on  (Volume:6 )

Date of Conference: