Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2015
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dc.contributor.authorGüdelek, Mehmet Uğur-
dc.contributor.authorÇırak, C. R.-
dc.contributor.authorArın, E.-
dc.contributor.authorSezgin M. E.-
dc.contributor.authorÖzbayoğlu, Ahmet Murat-
dc.contributor.authorGol, M.-
dc.date.accessioned2019-07-10T14:42:46Z-
dc.date.available2019-07-10T14:42:46Z-
dc.date.issued2018-11-20-
dc.identifier.citationGudelek, M. U., Cirak, C. R., Arin, E., Sezgin, M. E., Ozbayoglu, A. M., & Gol, M. (2018, September). Load and PV Generation Forecast Based Cost Optimization for Nanogrids with PV and Battery. In 2018 53rd International Universities Power Engineering Conference (UPEC) (pp. 1-6). IEEE.en_US
dc.identifier.isbn978-153862910-9-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8541882/-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/2015-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8541882en_US
dc.description53rd International Universities Power Engineering Conference (2018 : United Kingdom)-
dc.description.abstractPower system resiliency and robustness became major concerns of the system operators and researchers after the introduction of the smart grid concept. The improvements in the battery storage systems (BSS) and the photovoltaic (PV) systems encourage power systems operators to enable the use of those systems in resiliency and robustness studies. Utilization of those systems not only contributes to the robustness of the power systems but also decrease the operational costs. There are several methods in literature to operate the grid systems with partitions of PV and BSS in the most economical way. Although these methods are straightforward and work fine, they can not guarantee the most economical result on a daily basis. In this paper, deep learning based PV generation and load forecasts are used to improve the results of optimization in terms of economic aspects in nano-grid applications. In the considered system, there are loads, PV generation units, BSS and grid connection. Bi-directional power flow is permitted between the main grid and the nano-grid system. The forecasting methodologies and used optimization algorithms will be explained in this paper. © 2018 IEEE.en_US
dc.description.sponsorshipEDF,IEEE,RTDS Technologies,Scottish and Southern Electricity Networks,TJ - H2b-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2018 53rd International Universities Power Engineering Conferenceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSolar radiationen_US
dc.subjectSolar energyen_US
dc.subjectDaily globalen_US
dc.titleLoad and Pv Generation Forecast Based Cost Optimization for Nanogrids With Pv and Batteryen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.authorid0000-0001-7998-5735-
dc.identifier.wosWOS:000468972100037en_US
dc.identifier.scopus2-s2.0-85059949170en_US
dc.institutionauthorÖzbayoğlu, Ahmet Murat-
dc.identifier.doi10.1109/UPEC.2018.8541882-
dc.authorwosidH-2328-2011-
dc.authorscopusid6505999525-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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