Lightning performance identification of high voltage transmission lines using artificial, neural networks

The paper presents a novel approach to lightning performance identification of high voltage transmission lines using artificial neural networks (ANNs). This approach is described in detail and results obtained by its application on an operating 400 kV Hellenic transmission line are presented. The conventional multilayer perceptron (MLP) technique, based on a backpropagation algorithm was considered in order to train the model. Actual input and output data collected from operating Hellenic high voltage transmission lines were used in the training process. The computed lightning failure rate is compared with real records of outage rate and with results obtained using the analytical algorithms. The presented methodology can be proved valuable to the studies of electric power systems designers, intended in a more effective protection of transmission lines against lightning strokes.