Designing a smart home energy management system to improve cost/comfort factor;

dc.authorscopusid55780618800
dc.authorscopusid57197026443
dc.authorscopusid6701741537
dc.authorscopusid14830500900
dc.authorscopusid57194316958
dc.authorscopusid57202403035
dc.contributor.authorKıvanç,Ö.C.
dc.contributor.authorAkgün,B.T.
dc.contributor.authorBilgen,S.
dc.contributor.authorÖztürk,S.B.
dc.contributor.authorBaysan,S.
dc.contributor.authorTuncay,R.N.
dc.contributor.otherBilgisayar Mühendisliği / Computer Engineering
dc.date.accessioned2024-05-25T12:33:15Z
dc.date.available2024-05-25T12:33:15Z
dc.date.issued2020
dc.departmentOkan Universityen_US
dc.department-tempKıvanç Ö.C., Elektrik-Elektronik Mühendisliği Bölümü, Mühendislik Fakültesi, İstanbul Okan Üniversitesi, Tuzla, İstanbul, Turkey; Akgün B.T., Bilgisayar Mühendisliği Bölümü, Mühendislik Fakültesi, İstanbul Okan Üniversitesi, Tuzla, İstanbul, Turkey; Bilgen S., Bilgisayar Mühendisliği Bölümü, Mühendislik Fakültesi, İstanbul Okan Üniversitesi, Tuzla, İstanbul, Turkey; Öztürk S.B., Elektrik Mühendisliği Bölümü, Elektrik-Elektronik Fakültesi, İstanbul Teknik Üniversitesi, Maslak, İstanbul, Turkey; Baysan S., ACMENA Teknoloji Yönetim ve Yatırım Hizmetleri A.Ş., Turkey; Tuncay R.N., Elektrik-Elektronik Mühendisliği Bölümü, Mühendislik Fakültesi, İstanbul Okan Üniversitesi, Tuzla, İstanbul, Turkeyen_US
dc.description.abstractHome energy management systems optimize the energy buying/selling amount to reduce high costs by increasing individual energy consumption. Shifting the consumption time depending on the tariff is provided as cost, and the more effective and automatic operation of the devices is offered to the user as comfort. In the study, a hardware and software are developed that can estimate solar energy potential, energy consumption and automatically regulate the comfort/cost ratio of domestic energy using these data. Battery status, electricity buying/selling price, weather condition and consumption forecast data are evaluated by fuzzy logic algorithm and provide the ratio of comfort and cost effectiveness. The obtained comfort and cost effectiveness determine the optimum energy supply amount between the battery, grid and solar energy using the simulated annealing algorithm. As a result of the study, it has been determined that the energy cost for the user has decreased and the comfort has increased. © 2020 Turkish Chambers of Electrical Engineers.en_US
dc.identifier.citation1
dc.identifier.doi10.1109/ELECO51834.2020.00059
dc.identifier.endpage48en_US
dc.identifier.isbn978-605011331-0
dc.identifier.scopus2-s2.0-85100541319
dc.identifier.startpage44en_US
dc.identifier.urihttps://doi.org/10.1109/ELECO51834.2020.00059
dc.identifier.urihttps://hdl.handle.net/20.500.14517/2464
dc.institutionauthorBilgen, Semih
dc.institutionauthorBilgen, Semih
dc.institutionauthorBilgen S.
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2020 12th International Conference on Electrical and Electronics Engineering, ELECO 2020 -- 12th International Conference on Electrical and Electronics Engineering, ELECO 2020 -- 26 November 2020 through 28 November 2020 -- Bursa -- 166560en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keyword Available]en_US
dc.titleDesigning a smart home energy management system to improve cost/comfort factor;en_US
dc.title.alternativeMaliyet/Konfor Faktörünü İyileştirmeye Yönelik bir Akıllı Ev Enerji Yönetim Sistemi Tasarımıen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
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