Real-time security monitoring of electric power systems using parallel associative memories

A methodology for the monitoring of power system security, developed with emphasis on the efficient processing of large amounts of data gathered through communication channels in real time, is presented. The approach is based on the adaptive pattern recognition concept and its implementation on parallel distributed computational architectures of artificial neural networks. Clusterwise continuous associative maps are established through data self-organization encompassing a variety of system operating regimes and topological configurations of the transmission network. Accurate and very fast information retrieval characterizes the real-time behavior of the distributed information processing system.<
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