Title: Classification and location of single line to ground faults in double circuit transmission lines using artificial neural networks
Authors: Anamika Jain, A.S. Thoke, R.N. Patel, Pawan K. Modi
Addresses: Department of Electrical Engineering, National Institute of Technology, Raipur, 492010, C.G., India. ' Department of Electrical Engineering, National Institute of Technology, Raipur, 492010, C.G., India. ' Department of Electrical and Electronics, S.S. College of Engineering and Technology, Bhilai 490020, Chhattisgarh, India. ' Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla 768018, Orissa, India
Abstract: Fault detection, classification and location from the relay end in a double circuit transmission line are challenging tasks because of mutual coupling between the two circuits. In this paper, combined unsupervised and supervised neural networks-based fault detection, classification and distance location techniques are presented for a double circuit line. This technique does not require communication link to retrieve the remote end data. Zero sequence current compensation for healthy phases can also be avoided. Artificial neural network employs a reduced set of input features, i.e., the fundamental components of three phase voltages and the six phase currents of the two parallel lines at one end of the line only. The simulation results show that single phase-to-ground faults can be correctly classified and located after one cycle from the inception of fault. The complexity of the possible types of faults, fault locations, high path fault resistances, fault inception angles, mutual coupling effects and remote end in-feed do not affect the performance.
Keywords: double circuit transmission lines; distance protection; fault location; fault classification; artificial neural networks; ANNs; fault detection; simulation; high path fault resistance; fault inception angles; mutual coupling; remote end in-feed.
International Journal of Power and Energy Conversion, 2010 Vol.2 No.2, pp.109 - 125
Received: 10 Jun 2009
Accepted: 27 Oct 2009
Published online: 21 Nov 2010 *