DocumentCode :
1897499
Title :
ANN based fault detection & direction estimation scheme for series compensated transmission lines
Author :
Verma, Aditi ; Yadav, Anamika
Author_Institution :
Dept. of Electr. Eng., Nat. Inst. of Technol., Raipur, India
fYear :
2015
fDate :
5-7 March 2015
Firstpage :
1
Lastpage :
6
Abstract :
In this paper a directional relaying scheme for fixed series capacitor compensated transmission lines is proposed using Artificial Neural Network (ANN). The fundamental voltage and current signals are used as input to Artificial Neural Network which detects the fault on the transmission line and identifies the section of the fault. Different parameters like fault type, fault location, fault inception angle, and fault resistance are varied to evaluate the performance of the proposed scheme. A large number of fault cases studies have been performed to test the efficiency of the proposed scheme. Test results show the accuracy and effectiveness of proposed algorithm. Relay operation time is within half cycle for the proposed method. Accuracy of fault detection scheme is 99% and section identification scheme is 100%.
Keywords :
fault diagnosis; neural nets; power engineering computing; power transmission faults; power transmission lines; relay protection; ANN based fault detection scheme; ANN based fault direction estimation scheme; artificial neural network; directional relaying scheme; fixed series capacitor compensated transmission line; fundamental current signal; fundamental voltage signal; relay operation time; section identification scheme; Artificial neural networks; Classification algorithms; MATLAB; Relays; Artificial neural network; directional relay; fault detection; series compensation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6084-2
Type :
conf
DOI :
10.1109/ICECCT.2015.7225958
Filename :
7225958
Link To Document :
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