Artificial neural networks and their application to power system industry

A method to apply neural-network technology to the study of transient stability of electric power systems is presented. During the training phase the network is presented with a set of input and output data obtained from an offline study. After the network has obtained the ability to compute the desired output, the network is presented with the data representing different operating conditions for critical cleaning time estimation. An attempt is made to present a design philosophy to determine the most effective architecture for this problem.<
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