Title :
A new fast method for supplying measures to avoid the high voltage mode of electromagnetic voltage transformer
Author :
Jilai, Yu ; Zhizhong, Guo ; Zhuo, Liu
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., China
Abstract :
A new fast method for supplying preventive measures to avoid the failure of electromagnetic voltage transformers (EMVT) due to sustained overvoltage on switch-off is proposed. This method makes full use of the characteristics of artificial neural networks and utilizes the Kohonen network model to design a classifier which can fast supply a satisfactory solution to prevent EMVT damage due to a sustained overvoltage on switch-off. Tests on a 110 kV EMVT show that the fast method has improved protection performance
Keywords :
digital control; neural nets; overvoltage protection; potential transformers; power engineering computing; power transformers; switching; transformer protection; 110 kV; Kohonen network model; artificial neural networks; electromagnetic voltage transformer; failure; high voltage; overvoltage; power transformer protection; switching; Artificial neural networks; Biology computing; Capacitance; Circuit breakers; Circuit testing; Electric variables measurement; Electromagnetic measurements; Network topology; Neural networks; Voltage transformers;
Conference_Titel :
Neural Networks to Power Systems, 1991., Proceedings of the First International Forum on Applications of
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0065-3
DOI :
10.1109/ANN.1991.213460
