access icon free Fuzzy based methodologies comparison for high-impedance fault diagnosis in radial distribution feeders

© The Institution of Engineering and Technology
Received 05/09/2016, Accepted 17/01/2017, Revised 25/11/2016, Published 23/01/2017

This study presents a comparison of two developed intelligent systems that carries out, in an integrated manner, failure diagnosis on electric power distribution feeders. These procedures aim to identify and classify critical situations, as high-impedance faults, which can potentially damage the system components and cause power supply interruptions to consumers. The intelligent systems combine the wavelet transform, Dempster–Shafer evidence theory, voting scheme, fuzzy inference system and artificial neural networks. Results show the efficiency, reliability, and robustness of the proposed methodology, allowing its real-time application.

Inspec keywords: power engineering computing; fuzzy reasoning; power distribution faults; neural nets; wavelet transforms; fuzzy set theory; fault diagnosis

Other keywords: power supply interruptions; fuzzy based methodology; Dempster-Shafer evidence theory; artificial neural networks; radial distribution feeders; voting scheme; high-impedance fault diagnosis; , fuzzy inference system; intelligent systems; wavelet transform; electric power distribution feeders; system components

Subjects: Knowledge engineering techniques; Power engineering computing; Neural computing techniques; Combinatorial mathematics; Integral transforms; Integral transforms; Distribution networks; Combinatorial mathematics

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