Full metadata record
DC poleHodnotaJazyk
dc.contributor.authorAslani, Mehrdad
dc.contributor.authorFaraji, Jamal
dc.contributor.authorHashemi Dezaki, Hamed
dc.contributor.authorKetabi, Abbas
dc.date.accessioned2022-06-06T10:00:30Z-
dc.date.available2022-06-06T10:00:30Z-
dc.date.issued2022
dc.identifier.citationASLANI, M. FARAJI, J. HASHEMI DEZAKI, H. KETABI, A. A novel clustering-based method for reliability assessment of cyber-physical microgrids considering cyber interdependencies and information transmission errors. APPLIED ENERGY, 2022, roč. 315, č. June 2022, s. 1-21. ISSN: 0306-2619cs
dc.identifier.issn0306-2619
dc.identifier.uri2-s2.0-85127122024
dc.identifier.urihttp://hdl.handle.net/11025/47718
dc.format21 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherElsevieren
dc.relation.ispartofseriesApplied Energyen
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© Elsevieren
dc.titleA novel clustering-based method for reliability assessment of cyber-physical microgrids considering cyber interdependencies and information transmission errorsen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn recent years, the evolution of microgrids (MGs) toward a complex interacted cyber-physical system is significant, which has received much attention. Cyber-physical MGs (CPMGs) are vulnerable to various cyberphysical interdependencies mainly. Therefore, the reliability evaluation of such systems is a crucial issue. Several research works have focused on the reliability assessment of CPMGs in the literature. However, there is a research gap in developing fast and accurate models to assess the reliability of CPMGs, simultaneously considering cyber and physical failures, cyber-power interdependencies, and information transmission errors. This article aims to fill such a knowledge gap by developing a new clustering-based method to evaluate the reliability of CPMGs. The scenarios for information transmission errors are generated by the Monte Carlo simulation (MCS), besides uncertain physical parameters, e.g., the output power of renewable distributed generations (DGs). Afterward, the clustering algorithms are used to reduce the number of scenarios. In this paper, the k-means clustering algorithm has been selected to cluster the scenarios. The introduced clustering-based method is applied to a CPMG, and test results are compared to available MCS-based studies. The inaccuracy of the proposed clustering-based method is less than 3%, while its execution time is about 22 times faster than MCS-based ones. The comparative test results under various scenarios like available methods, neglecting the cyber failures and information errors illustrate the advantages of this research. The comparative test results illustrate the accuracy of the reliability calculations, while the execution time is desired.en
dc.subject.translatedcyber-physical systemsen
dc.subject.translatedmicrogridsen
dc.subject.translatedreliability assessmenten
dc.subject.translatedclustering algorithmen
dc.subject.translatedMonte Carlo simulationen
dc.subject.translatedinformation transmission errorsen
dc.identifier.doi10.1016/j.apenergy.2022.119032
dc.type.statusPeer-revieweden
dc.identifier.document-number793663600003
dc.identifier.obd43936023
Vyskytuje se v kolekcích:Články / Articles (RICE)
OBD

Soubory připojené k záznamu:
Soubor VelikostFormát 
Dezaki_1-s2.0-S0306261922004378-main.pdf11,53 MBAdobe PDFZobrazit/otevřít  Vyžádat kopii
Zobrazit minimální záznam Zobrazit statistiky


Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/47718

Všechny záznamy v DSpace jsou chráněny autorskými právy, všechna práva vyhrazena.

hledání
navigace
  1. DSpace at University of West Bohemia
  2. Publikační činnost / Publications
  3. OBD