Abstract
This paper presents differential protection and condition monitoring scheme for power transformer using ANN. This ANN-based scheme monitors different operating conditions of the transformer, detects the fault, and issues the trip signal in case of internal fault only. The proposed protection scheme is accurate, fast, efficient, and reliable. This scheme has been realized through two different ANN structures using the Radial Basis Function (RBF) learning algorithm. The proposed protection scheme has been evaluated using simulated data obtained through EMTP/ATP package. The results amply demonstrate the capabilities of Fault Detector (FD) and Condition Monitor (CM) in terms of accuracy and speed with respect to detection of fault, classification, and pattern recognition of different events of power transformer.
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