Technical assessment of solar energy storage investments with recommender system-enhanced quantum picture fuzzy rough sets

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dc.contributor.authorKou, Gang
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.contributor.authorEti, Serkan
dc.contributor.authorAcar, Merve
dc.date.accessioned2025-11-11T08:50:12Z
dc.date.available2025-11-11T08:50:12Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, İMÜ Meslek Yüksekokulu, Bilgisayar Programcılığı Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
dc.description.abstractThe performance of solar energy storage projects should be improved by taking appropriate actions. However, there are very different criteria that affect the performance of these investments. Therefore, businesses need to focus on more important criteria to use the budget effectively and efficiently. This situation increases the need for a priority analysis for performance indicators of solar energy storage investments. Accordingly, the purpose of this study is to make evaluation for the technical assessment of solar energy storage investments. In this scope, a new four-stage model is introduced by considering different decision-making techniques and fuzzy sets. The first stage is related to the prioritizing the experts with artificial intelligence (AI)-based decision-making method. Secondly, the missing evaluations of solar energy storage investments are estimated with expert recommender system. In the following part, the criteria for the technical assessment of solar energy storage investments are weighted by quantum picture fuzzy rough sets (QPFRS) adopted M−SWARA. The final stage consists of ranking the solar energy storage alternatives with QPFR-VIKOR. The main contribution of this study is the generation of the decision matrix by the help of AI. This situation gives an opportunity to calculate the significance weights of the experts. Therefore, the analysis results can be more reliable and coherent. It is concluded that battery capacity is the most critical factor for the technical assessment of solar energy storage investments. On the other hand, pumped hydro for mechanic energy is found as the most significant solar energy storage alternative. Governments should provide the necessary incentives for the development of high-capacity battery technologies. In this context, tax reductions can be provided to companies that invest in production technologies. This contributes to the cost efficiency of businesses.
dc.identifier.citationKou, G., Dinçer, H., Yüksel, S., Eti, S. ve Acar, M. (2024). Technical assessment of solar energy storage investments with recommender system-enhanced quantum picture fuzzy rough sets. International Journal of Electrical Power and Energy Systems, 163. http://dx.doi.org/10.1016/j.ijepes.2024.110361
dc.identifier.doi10.1016/j.ijepes.2024.110361
dc.identifier.issn0142-0615
dc.identifier.issn1879-3517
dc.identifier.scopus2-s2.0-85208466332
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.ijepes.2024.110361
dc.identifier.urihttps://hdl.handle.net/20.500.12511/13188
dc.identifier.volume163
dc.identifier.wosWOS:001356131000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.institutionauthorEti, Serkan
dc.institutionauthorAcar, Merve
dc.institutionauthorid0000-0002-8072-031X
dc.institutionauthorid0000-0002-9858-1266
dc.institutionauthorid0000-0002-4791-4091
dc.institutionauthorid0000-0001-5853-4943
dc.language.isoen
dc.relation.ispartofInternational Journal of Electrical Power and Energy Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectEnergy Storage Investments
dc.subjectRecommender System
dc.subjectSolar Energy Storage
dc.subjectTechnical Assessment
dc.titleTechnical assessment of solar energy storage investments with recommender system-enhanced quantum picture fuzzy rough sets
dc.typeArticle

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