Bidding and Operating Planning of a Virtual Power Plant in a Day-Ahead Market

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dc.contributor.authorAkkaş, Özge Pınar
dc.contributor.authorÇam, Ertuğrul
dc.date.accessioned2025-01-21T16:18:32Z
dc.date.available2025-01-21T16:18:32Z
dc.date.issued2020
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn this study, it is aimed to determine the optimum bidding and operating planning of a Virtual Power Plant (VPP) in the energy market to obtain maximum profit. For this purpose, the VPP containing a Wind Power Plant (WPP), a Photovoltaic Power Plant (PVPP), and an Energy Storage System (ESS) is composed on the IEEE 6-bus test system with Distributed Generators (DGs). The bidding planning and operating scheduling of the components of the VPP participating in the Day-ahead Market (DAM) are decided hourly for a day. Thus, SGS is aimed to gain maximum profit. The proposed problem has been modeled as Mixed Integer Linear Programming (MILP) in GAMS software and solved with CPLEX solver to obtain optimum results. The obtained results show that the model is applicable and the method is valid.
dc.identifier.doi10.29137/umagd.842476
dc.identifier.endpage10
dc.identifier.issn1308-5514
dc.identifier.issue3
dc.identifier.startpage1
dc.identifier.trdizinid475410
dc.identifier.urihttps://doi.org/10.29137/umagd.842476
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/475410
dc.identifier.urihttps://hdl.handle.net/20.500.12587/22887
dc.identifier.volume12
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofUluslararası Mühendislik Araştırma ve Geliştirme Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectMühendislik
dc.subjectElektrik ve Elektronik
dc.subjectBilgisayar Bilimleri
dc.subjectYazılım Mühendisliği
dc.subjectİşletme
dc.subjectEnerji ve Yakıtlar
dc.subjectİktisat
dc.subjectİşletme Finans
dc.titleBidding and Operating Planning of a Virtual Power Plant in a Day-Ahead Market
dc.typeArticle

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