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Early warning fault detection using artificial intelligent methods

By K. C. P. Wong, H. M. Ryan and J. Tindle

Abstract

This paper describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system. Artificial Neural Networks (ANNs) are being used as the core of the fault detector. A simulated medium length transmission line has been tested by the detector and the results demonstrate the capability of the detector. Furthermore, comments on an evolutionary technique as the optimisation strategy for ANNs are included in this paper

Publisher: Technological Educational Institute of Iraklion
Year: 1996
OAI identifier: oai:oro.open.ac.uk:17761
Provided by: Open Research Online

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