Title :
Improving Synchronous Generator´s differential protection with the use of Artificial Neural Networks
Author :
Monaro, R.M. ; Silva, R.C.S. ; de Melo Vieira, Jose Carlos ; Coury, D.V.
Author_Institution :
Dept. of Electr. Eng., Univ. of Sao Paulo, São Carlos, Brazil
Abstract :
This paper presents an alternative technique to detect and correct waveforms distortion due to Current Transformer (CT) saturation using intelligent tools based on Artificial Neural Network (ANN). The Real-time Digital Simulator (RTDS) was used to evaluate the performance of the ANNs running in a real-time embedded system. It is also shown that the CT saturation influences the Synchronous Generator (SG) differential protection.
Keywords :
electric machine analysis computing; embedded systems; neural nets; power system protection; synchronous generators; ANN; CT saturation; RTDS; SG differential protection; artificial neural networks; current transformer saturation; intelligent tools; realtime digital simulator; realtime embedded system; synchronous generator differential protection; waveforms distortion; Artificial neural networks; Circuit faults; Current transformers; Data acquisition; Fault currents; Relays; Training; Artificial Neural Network; Correction; Current Transformer; Detection; Differential Protection; RTDS; Saturation; Synchronous Generator;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6344704
