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A comprehensive fuzzy-based scheme for online detection of operational and topological changes

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 4 (2022)

DOI
10.11591/ijece.v12i4.pp3396-3409
ISSN
2722-2578, 2088-8708
Published
2022-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Operational modes and topological changes affect power flow in the power systems. As a result, a broad spectrum of protection issues may happen in the power system. So, both the operational and topological changes should be detected fast to prevent blackouts. On the other hand, the existing detection schemes are complex in analyzing and implementation. Therefore, there is a need for an online scheme to identify the network's topology and operation mode simultaneously without complex computations and additional communication infrastructures. To this end, a comprehensive scheme is proposed in which the changes are detected by analyzing the power flow obtained from the network. For this purpose, line outage contingencies and operation modes are defined in rules to be used in a fuzzy inference system (FIS) as a decision-making tool. The proposed scheme can be implemented on existing lines as a communication infrastructure and determines the network’s status in an online manner. Also, in comparison to the existing schemes, the proposed scheme reduces the complexity and the computational burden. The proposed scheme is implemented on IEEE 8-bus system and the results proved its efficiency.

Collaboration network of the authors

5 authors · 8 co-authorship links

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  • Islamic Azad University, Tehran
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Seyed Ali HosseiniIslamic Azad University, Tehran2

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
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