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Power factor correction in power systems having load asymmetry by using fuzzy logic controller

dc.contributor.authorTanrioven, M
dc.contributor.authorKocatepe, C
dc.contributor.authorUnal, A
dc.date.accessioned2026-06-27T12:56:06Z
dc.date.issued1997
dc.description.abstractAs known, the studies on power factor correction have been carried out for many years. But in these studies, generally, phase powers received from supply are assumed to be balanced. In the paper, power systems having unbalanced load are considered. The fuzzy logic controller based on the fuzzy set theory provides a useful tool for converting the linguistic control from the expert knowledge into automatic control rules. By using fuzzy automatic rules from the heuristic or mathematical strategies, complex processes can be controlled effectively in many situations.[1] But the most important and difficult point is how to obtain the proper control rules for a given system. In this paper, power factor correction is corrected to demand value by using fuzzy logic controller for the electric power system containing current unbalance i.e. load asymmetry. As well as this, generalized fuzzy logic controller was resembled by writing its software in Q - basic programming language. Consequently, the software of the system's simulation results were given for power factor correction in the power systems having load asymmetry. In addition to that, the developed method is compared according to conventional compensation systems.en
dc.identifier.endpage535
dc.identifier.isbn3-540-62868-1
dc.identifier.issn0302-9743
dc.identifier.startpage529
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47835
dc.identifier.volume1226
dc.identifier.wos000073946500055
dc.language.isoeng
dc.publisherSPRINGER-VERLAG BERLIN
dc.relation.conference5th Fuzzy Days International Conference on Computational Intelligence
dc.relation.ispartofCOMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS
dc.subjectComputer Science
dc.titlePower factor correction in power systems having load asymmetry by using fuzzy logic controller
dc.typeArticle; Proceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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