A new intelligent decision-maker method determining the optimal connection point and operating conditions of hydrogen energy-based DGs to the main grid

Basit Öğe Kaydı
dc.authorid0000-0002-5136-0829
dc.authorid0000-0003-3736-3668
dc.contributor.authorBayrak, Gokay
dc.contributor.authorYilmaz, Alper
dc.contributor.authorCalisir, Alperen
dc.date.accessioned2026-02-12T21:05:24Z
dc.date.available2026-02-12T21:05:24Z
dc.date.issued2023
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThis study presents a new two-step intelligent decision-maker method using hydrogen energy-based distributed generators (HEDGs) to contribute to the reliability, durability, and stability of power transmission system in Bursa. In the first stage, the proposed method uses the power flow parameters evaluation (PFPE) algorithm to define the possible appropriate connection point of HEDGs by determining the electrical parameters. Then, to determine the conditions in which the HEDGs connected to the grid should be switched on, the power flow data such as load status, bus bar powers, and, line capacities are evaluated with the artificial neural network (ANN)-based method with a scaled conjugate gradient (SCG) algorithm. With the proposed intelligent two-step decision-maker method, HEDGs are connected to the points determined using the PFPE algorithm, and then the appropriate operating conditions for which HEDGs should be enabled are determined by the ANN with SCG. Different combinations of load status, bus bar powers, and line capacities values are applied to the ANN input and important features are determined. The ANN with SCG can predict the operating conditions of HEDGs with 96.8% accuracy in the test set and, 98.4% accuracy in the validation set. Thanks to the developed holistic PFPE & ANN approach, op-timum connection points and suitable operating conditions can be determined, which ensures reliability and safety for HEDGs in overload and/or failure conditions. & COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.ijhydene.2023.02.043
dc.identifier.endpage23184
dc.identifier.issn0360-3199
dc.identifier.issn1879-3487
dc.identifier.issue60
dc.identifier.scopus2-s2.0-85149782759
dc.identifier.scopusqualityQ1
dc.identifier.startpage23168
dc.identifier.urihttps://doi.org/10.1016/j.ijhydene.2023.02.043
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6949
dc.identifier.volume48
dc.identifier.wosWOS:001035480800001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofInternational Journal of Hydrogen Energy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260212
dc.subjectHydrogen energy
dc.subjectEnergy management
dc.subjectNeural network
dc.subjectGrid integration
dc.subjectDistributed generation
dc.titleA new intelligent decision-maker method determining the optimal connection point and operating conditions of hydrogen energy-based DGs to the main grid
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu