Recently, several neural network techniques have been proposed to solve the problem of automatic fault diagnosis in power systems. In this paper, a new and accurate parallel neural network-based approach for fast fault diagnosis and alarm handling of power systems is developed which overcomes some of the limitations of existing techniques. Three different neural-network configurations are proposed and their performances arc compared using the data of an actual high-voltage power network.
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