Neural network based fault diagnosis in an HVDC system

Neural network based fault diagnosis in an HVDC system

This paper presents a neural network (NN) based method for fault classification in a power system. A new method of generating the training data is proposed which has the advantage that the total number of fault simulations needed to generate the training patterns is less than that required by the co...

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Bibliographische Detailangaben
Hauptverfasser: Etemadi, H., Sood, V.K., Khorasani, K., Patel, R.V.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Circuit faults
Delay effects
Fault diagnosis
HVDC transmission
Input variables
Intelligent networks
Neural networks
Power system modeling
Power system simulation
Training data
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Beschreibung
Zusammenfassung:This paper presents a neural network (NN) based method for fault classification in a power system. A new method of generating the training data is proposed which has the advantage that the total number of fault simulations needed to generate the training patterns is less than that required by the conventional training method. This is obtained at the cost of a time delay in the NN output response. The performance of the proposed method is investigated using the Matlab simulation model of a simple HVDC system.
DOI:10.1109/DRPT.2000.855665