Title :
Artificial neural networks applied in study of atmospheric parameters to high voltage substations concerning lightning
Author :
De Souza, André N. ; da Silva, Ivan N. ; Bordon, Mario E.
Author_Institution :
Dept. of Electr. Eng., Sao Paulo Univ., Brazil
Abstract :
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
Keywords :
feedforward neural nets; lightning protection; parameter estimation; power engineering computing; substations; ANN; atmospheric factors; atmospheric parameters; critical disruptive voltage; electrical field intensity; feedforward artificial neural networks; high-voltage substations; humidity; lightning; parameter estimation; pressure; temperature; Artificial neural networks; Atmospheric modeling; Computational modeling; Computer networks; Humidity; Parameter estimation; Substations; Temperature; Testing; Voltage;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.859394
