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Traveling wave based fault location for power transmission lines using morphological filters and clarke modal components

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp1122-1134
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

This article presents a fast and accurate fault location approach for power transmission lines based on the theory of traveling waves. In fact, when faults occur, they give rise to transient voltages and currents that propagate at a speed close to that of light along the transmission line as traveling waves. Moreover, according to the superposition theorem, each of these transients is a combination of a steady-state quantity and an incremental quantity. These transient signals measured at both ends of the line are first transformed to the Clarke (0-α-β components) components in order to categorize the type of faults, and then multi-scale morphological gradient filters are used to extract equivalent quantities to the incremental quantities to form what are called characteristic signals. These latter will be used to identify the fault location according to the proposed algorithm.

Collaboration network of the authors

16 authors · 47 co-authorship links · 4 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Hassan II Casablanca
  • Cadi Ayyad University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mohamed Nouh DazahraAffiliation unknown12
Faissal El MariamiUniversity of Hassan II Casablanca10
Tayeb OuaderhmanUniversity of Hassan II Casablanca10
Nazha CherkaouiAffiliation unknown6
Anass LekbichUniversity of Hassan II Casablanca5
Abdelmajid BerdaiUniversity of Hassan II Casablanca4
Chaimae ZedakUniversity of Hassan II Casablanca3
Ali TarraqUniversity of Hassan II Casablanca2
Touria HaidiUniversity of Hassan II Casablanca2
Naima AgouzoulUniversity of Hassan II Casablanca2
Aziz OukennouCadi Ayyad University2
Rabiaa GadalUniversity of Hassan II Casablanca2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Traveling wave based fault location for power transmission lines using morphological filters and clarke modal components</dc:title><dc:creator>Khoudry, Elmahdi</dc:creator><dc:creator>Belfqih, Abdelaziz</dc:creator><dc:creator>Boukherouaa, Jamal</dc:creator><dc:creator>Elmariami, Faissal</dc:creator><dc:description>&lt;jats:p&gt;This article presents a fast and accurate fault location approach for power transmission lines based on the theory of traveling waves. In fact, when faults occur, they give rise to transient voltages and currents that propagate at a speed close to that of light along the transmission line as traveling waves. Moreover, according to the superposition theorem, each of these transients is a combination of a steady-state quantity and an incremental quantity. These transient signals measured at both ends of the line are first transformed to the Clarke (0-α-β components) components in order to categorize the type of faults, and then multi-scale morphological gradient filters are used to extract equivalent quantities to the incremental quantities to form what are called characteristic signals. These latter will be used to identify the fault location according to the proposed algorithm.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v10i2.pp1122-1134</dc:identifier><dc:identifier>10.11591/ijece.v10i2.pp1122-1134</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 2 (2020); 1122</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/20834/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>