Title :
Improved ANN based impedance estimator for phase to ground faults in UHV transmission line
Author :
Rafique, Syed Furqan ; Xu, Z.Y. ; Khan, A. Zeb
Author_Institution :
Sch. of Electr. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
An accurate digital distance relaying scheme integrated with artificial neural network impedance estimator is developed using the weighted sum of the negative-zero sequence components of fault current assuming the voltage and current are in phase at the fault location. The modified scheme is immune to the variation in fault location for under reach and overreach problem caused by sequence current components. A series of test conducted on a 800kV, 400km transmission line for single phase to ground faults as well as simultaneous open conductor fault in PSCAD/EMTP and Matlab. Finally comparison has been done with the conventional methods in order to check the accuracy and robustness of the proposed scheme which is found to be 95%.
Keywords :
electric impedance; fault location; neural nets; power engineering computing; power transmission faults; transmission network calculations; ANN; UHV transmission line; artifical neural network; digital distance relaying; distance 400 km; fault current; fault location; impedance estimator; negative zero sequence components; phase-to-ground faults; voltage 800 kV; Artificial neural networks; Circuit faults; Conductors; Fault location; Impedance; Resistance; Transmission line measurements; Artificial neural network; Negative Zero sequence current; simultaneous fault;
Conference_Titel :
Intelligent Energy and Power Systems (IEPS), 2014 IEEE International Conference on
Conference_Location :
Kyiv
Print_ISBN :
978-1-4799-2265-9
DOI :
10.1109/IEPS.2014.6874161
