Application of artificial neural network methods for the lightning performance evaluation of Hellenic high voltage transmission lines

Feed-forward (FF) artificial neural networks (ANN) and radial basis function (RBF) ANN methods were addressed for evaluating the lightning erformance of high voltage transmission lines. Several structures, learning algorithms and transfer functions were tested in order to produce a odel with the best generalizing ability. Actual input and output data, collected from operating Hellenic high voltage transmission lines, as well s simulated output data were used in the training, validation and testing process. The aims of the paper are to describe in detail and compare the roposed FF and RBF ANN models, to state their advantages and disadvantages and to present results obtained by their application on operating ellenic transmission lines of 150 kV and 400 kV. The ANN results are also compared with results obtained using conventional methods and real ecords of outage rate showing a quite satisfactory agreement. The proposed ANN methods can be used by electric power utilities as useful tools or the design of electric power systems, alternative to the conventional analytical methods. 2006 Elsevier B.V. All rights reserved.