Signal processing-based automated fault detection methods for smart grids

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dc.authorid0000-0002-5136-0829en_US
dc.contributor.authorBayrak, Gökay
dc.contributor.authorYılmaz, Alper
dc.date.accessioned2021-03-20T20:27:00Z
dc.date.available2021-03-20T20:27:00Z
dc.date.issued2020
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractAutomated fault detection methods (AFDMs) are required to provide a more reliable and stable power system operation and protection. The faults in distributed generators (DGs) connected to the grid must be cleared on time according to the defined Grid Codes, so AFDMs are essential for DGs to improve a smart grid infrastructure. The application of the conventional fault detection methods is highly practical. Besides, difficulties in selecting threshold values, false detection conditions, noise effects in measurement, and uncertain fault conditions in several operating conditions make these methods less reliable. This chapter generally consists of five main sections. In the introduction, the current fault detection methods used in DG systems are examined. Then, intelligent power quality detection methods are classified, and AFDMs using signal processing techniques in literature are presented. In the second section, FT-based fault detection methods and, in the third section, WT-based fault detection methods are explained. In Section “Detection of Power Quality Events with Wavelet Transform”, different WT methods are also classified and examined. Section “Wavelet Transform-Based Power Quality Disturbance Detection” presents the experimental results obtained from a DG system in real time using the WT method. In this section, some power quality disturbances are investigated in real time by using WT method under different grid conditions. In the last section, the advantages of automatic fault detection methods based on signal processing are explained. As a result, this chapter will help the researchers about studying automated fault detection systems in smart grids consisting of distributed power generators. © Springer Nature Switzerland AG 2020.en_US
dc.identifier.doi10.1007/978-3-030-39986-3_4en_US
dc.identifier.endpage85en_US
dc.identifier.issn2522-8595
dc.identifier.scopus2-s2.0-85090520397en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage57en_US
dc.identifier.urihttp://doi.org/10.1007/978-3-030-39986-3_4
dc.identifier.urihttps://hdl.handle.net/20.500.12885/1396
dc.indekslendigikaynakScopusen_US
dc.institutionauthorBayrak, Gökay
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofEAI/Springer Innovations in Communication and Computingen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAutomated fault detectionen_US
dc.subjectDistributed generationen_US
dc.subjectSignal processing methodsen_US
dc.subjectSmart gridsen_US
dc.subjectWavelet transformen_US
dc.titleSignal processing-based automated fault detection methods for smart gridsen_US
dc.typeBook Chapteren_US

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