Fault Classification in EHV Transmission Lines Using Artificial Neural Networks
نویسنده
چکیده
This paper investigates a new approach based on Artificial Neural Networks (ANNs) for real-time fault classification in power transmission lines which can be used in digital power system protection. The technique uses sampled current and voltage data of each phase at one terminal as inputs to the corresponding ANN. The ANN outputs indicate the type of the fault within a time less than 5 ms. The ANN-based classifier is tested under different fault types, fault location, fault resistance and fault inception angle. All the test results show that the proposed fault classifier can be used for supporting a new generation of very high speed protective relaying systems.
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