Intelligent power quality disturbance detection methods in virtual power plants: state-of-the-art

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dc.contributor.authorBayrak, Gökay
dc.contributor.authorYılmaz, Alper
dc.date.accessioned2026-02-08T15:11:07Z
dc.date.available2026-02-08T15:11:07Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThe objective of this research is to identify and categorize power quality disturbances (PQDs), specifically in the context of virtual power stations (VPPs). VPPs have become a hot topic in recent years, and this study discusses their definition, differences from microgrids, exemplary applications worldwide, integration criteria and related standards, planning parameters, and an example application in Gökçeada, Turkey. The study also created a model for a VPP in Gökçeada, Turkey, and examined the system responses in various faults scenarios. The results of the study show that VPPs can effectively address PQDs and faults. The study demonstrates the importance of effective planning parameters in the establishment of VPPs. Additionally, the study highlights the need for advanced detection and classification methods for PQDs in VPPs. Overall, this study provides a comprehensive analysis of VPPs and their applications in addressing PQDs. The research outcomes are expected to enhance the efficiency and dependability of VPPs through valuable insights into the classification of intelligent PQDs. © 2024 Elsevier Inc. All rights reserved.
dc.identifier.doi10.1016/B978-0-443-15806-3.00009-7
dc.identifier.endpage290
dc.identifier.isbn9780443158070
dc.identifier.isbn9780443158063
dc.identifier.scopus2-s2.0-85190018373
dc.identifier.scopusqualityN/A
dc.identifier.startpage267
dc.identifier.urihttps://doi.org/10.1016/B978-0-443-15806-3.00009-7
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5251
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.publicationcategoryKitap Bölümü - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzScopus_KA_20260207
dc.subjectartificial intelligence
dc.subjectdistributed generation
dc.subjectpower quality
dc.subjectsimulated VPP model
dc.subjectVirtual power plant (VPP)
dc.titleIntelligent power quality disturbance detection methods in virtual power plants: state-of-the-art
dc.typeBook Chapter

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