DocumentCode :
1691433
Title :
Application of neural network to microprocessor-based transformer protective relaying
Author :
Yongli, Li ; Jiali, He ; Yuqian, Duan
Author_Institution :
Dept. of Electr. Power & Autom. Eng., Tianjin Univ., China
Volume :
2
fYear :
1995
Firstpage :
680
Abstract :
A neural network method used to identify the operating states of transformers has been proposed and established. It is superior to the traditional transformer protective relays and can correctly identify, within half cycle from the fault inception, the internal faults, magnetizing inrush current state, external faults and switching on internal faults of a no-load transformer. In addition, this method has broad availability and high fault-tolerant ability. A lot of simulations have demonstrated its superiority
Keywords :
backpropagation; electrical faults; fault diagnosis; magnetisation; microcomputer applications; neural nets; power engineering computing; power transformer protection; relay protection; availability; backpropagation; external faults; fault diagnosis; fault inception; half cycle; high fault-tolerant ability; internal faults; magnetizing inrush current state; microprocessor-based transformer protective relaying; neural network method; no-load transformer; operating states identification; switching; Fault diagnosis; Neural networks; Power system harmonics; Power system protection; Power system relaying; Power system reliability; Power system simulation; Power transformers; Protective relaying; Surge protection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy Management and Power Delivery, 1995. Proceedings of EMPD '95., 1995 International Conference on
Print_ISBN :
0-7803-2981-3
Type :
conf
DOI :
10.1109/EMPD.1995.500810
Filename :
500810
Link To Document :
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