%0 Journal Article
%T Delta-Bar-Delta and directed random search algorithms to study capacitor banks switching overvoltages
%A Sadeghkhani Iman
%A Ketabi Abbas
%A Feuillet Rene
%J Serbian Journal of Electrical Engineering
%D 2012
%I Technical Faculty of ?a?ak
%R 10.2298/sjee1202217s
%X This paper introduces an approach to analyse transient overvoltages during capacitor banks switching based on artificial neural networks (ANN). Three learning algorithms, delta-bar-delta (DBD), extended delta-bar-delta (EDBD) and directed random search (DRS) were used to train the ANNs. The ANN training is based on equivalent parameters of the network and therefore, a trained ANN is applicable to every studied system. The developed ANN is trained with extensive simulated results and tested for typical cases. The new algorithms are presented and demonstrated for a partial 39-bus New England test system. The simulated results show the proposed technique can accurately estimate the peak values of switching overvoltages.
%K Artificial neural networks
%K Capacitor banks switching
%K Delta-bardelta
%K Directed random search
%K Switching overvoltages
%U http://www.doiserbia.nb.rs/img/doi/1451-4869/2012/1451-48691202217S.pdf