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

fYear

2014

fDate

2-6 June 2014

Firstpage

110

Lastpage

115

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Energy and Power Systems (IEPS), 2014 IEEE International Conference on

Conference_Location

Kyiv

Print_ISBN

978-1-4799-2265-9

Type

conf

DOI

10.1109/IEPS.2014.6874161

Filename

6874161