A Relaying Scheme for Detection and Classification of Shunt Faults in Six-Phase Transmission System Based on DFT-FIS Approach

  • Anamika Yadav National Institute of Technology, Raipur
  • V. Ashok National Institute of Technology, Raipur

Abstract

Hitherto many schemes based on the fuzzy system have been protected by a three-phase transmission system, but not bya six-phase transmission system. This paper sets out a novel protection scheme based on DFT-FIS approach for detection/classification of shunt faults in a six-phase transmission system. In this scheme, two separate DFT-FIS modules havebeen designed to detect the presence of fault in any of the six-phase(s) and to identify the presence of ground in the fault loop,thus classifying all 120 types of fault in a six-phase transmission line. The six-phase voltage and current signals are collectedat one end of the transmission line only, thus circumvent dependence on a communication link for remote end data. A widerangeof fault simulation studies were carried out in MATLAB/Simulink environment for all possible shunt fault combinationsby varying fault locations, fault inception angle, fault resistance, short circuit capacity (SCC) of the source and at various faultconditions such as: close-in faults, remote-end faults, high resistance faults, including CT saturation. Furthermore, the relayoperation time in fault detection/classification is less than one-cycle (<16.67ms) and since the scheme does not experienceany malfunction it is deemed reliable and adaptable.

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Published
2018-07-22
How to Cite
YADAV, Anamika; ASHOK, V.. A Relaying Scheme for Detection and Classification of Shunt Faults in Six-Phase Transmission System Based on DFT-FIS Approach. Journal of Power Technologies, [S.l.], v. 98, n. 2, p. 202–211, july 2018. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/1137>. Date accessed: 28 sep. 2021.
Section
Electrical Engineering

Keywords

Fuzzy Logic; Discrete Fourier Transform; fuzzy inference system; protective relaying; fault detection; fault classification;

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