Title :
New Artificial Neural Network Based Magnetizing Inrush Detection in Digital Differential Protection for Large Transformer
Author :
Lu, Yu-Ping ; Lai, L.L. ; Hua, Li-Dan
Author_Institution :
Dept of Electrical Engineering Southeast University, Nanjing, China 210096
Abstract :
The impact of inrush on large transformer differential protection has not been solved satisfactorily. A new intelligent ANN based scheme for digital differential protection is proposed in this paper to distinguish inrush from internal fault in a transformer. The new scheme is based on multi-condition restraint which introduces voltage features as a criterion. Test results show the advantages in comparing with traditional second harmonic restraint method. The new intelligent scheme can meet the requirements for large transformer protection.
Keywords :
Artificial neural network; differential protection; inrush; multi-condition restraint; transformer; Artificial intelligence; Artificial neural networks; Equations; Hardware; Intelligent networks; Power system harmonics; Power system protection; Power transformers; Surge protection; Testing; Artificial neural network; differential protection; inrush; multi-condition restraint; transformer;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1526987