Load Profile Analysis of Data Centers and IT Systems with Feature Effect Comparison

dc.contributor.authorKarabinaoglu, Murat Salim
dc.contributor.authorGözel, Tuba
dc.date.accessioned2025-10-29T11:36:42Z
dc.date.issued2018
dc.departmentFakülteler, Mühendislik Fakültesi, Elektronik Mühendisliği Bölümü
dc.descriptionIEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) -- OCT 21-25, 2018 -- Sarajevo, BOSNIA & HERCEG
dc.description.abstractLoad profile forecasting of a data center or IT system has recently been a challenging issue because of the huge consumption percentage of them within the global electricity supply. It is predicted that data centers will consume three times as much energy in next decade. The main goal of this paper is to find out which internal or external parameters are more or less effective for the power consumption of a data center by using a demo server device instead of a complicated data center. Specifically, the internal parameter analysis of a data center on power consumption by using automation control system devices, energy analyzers, appropriate custom designed software and etc. could make us to accomplish our aim regardless of the effect of cooling equipment on power consumption.
dc.description.sponsorshipIEEE,IEEE Power & Energy Soc
dc.description.sponsorshipGREENDC from the European Union [734273.]
dc.description.sponsorshipMarie Curie Actions (MSCA) [734273] Funding Source: Marie Curie Actions (MSCA)
dc.description.sponsorshipThis study has been funded by the GREENDC project from the European Union's Horizon 2020 research and innovation programme under grant agreement No 734273.
dc.identifier.isbn978-1-5386-4505-5
dc.identifier.issn2165-4816
dc.identifier.orcid0000-0003-4798-0635
dc.identifier.scopus2-s2.0-85060199205
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14854/13429
dc.identifier.wosWOS:000458690200075
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2018 IEEE Pes Innovative Smart Grid Technologies Conference Europe (Isgt-Europe)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20251020
dc.subjectdata center
dc.subjectIT System
dc.subjectartificial neural networks
dc.subjectregression
dc.subjectcorrelation
dc.titleLoad Profile Analysis of Data Centers and IT Systems with Feature Effect Comparison
dc.typeConference Object

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