Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Effects of a Period and a Contact Angle on Absorption Performance of Hemispherical-Shell-Shaped Organic Photovoltaic Cells(SPIE-Soc Photo-Optical Instrumentation Engineers, 2026-02-17) Hah, DooyoungFor wearable electronics applications, organic photovoltaic (OPV) cells are good candidates as sources of renewable energy. Many efforts have been devoted to increasing energy conversion efficiency in OPV cells, and improvement in light retention has been one of the main research directions. Within this context, our group recently proposed an OPV cell structure with a hemispherical-shell-shaped (HSS) active layer and discovered that it has high potential for substantial enhancement in absorption performance. As a continuation of the study, this paper reports an in-depth investigation of the proposed device, examining the effects of several design parameters on its absorption performance. Using finite element analysis, it is found that the absorption performance depends on the periodicity type, and that a hexagonal type results in higher absorption than a square one due to its closer shape resemblance to a circular cross-section. The absorption performance is also affected by a contact angle, i.e., the angle made between a sphere and a flat part of the structure. It is learned that the average integrated absorption generally increases along with the contact angle, which saturates at around 80 deg of contact angle. Lastly, the effects of a cell period are studied, and it turns out that the average integrated absorption decreases as the period increases. It is also observed that at high incidence angles (>similar to 75 deg ), an array with a shorter period results in lower absorption than one with a longer period owing to a partial obstruction issue. All of these results support the understanding that the primary contribution of absorption enhancement in the proposed HSS structure comes from improved light retention rather than from a simple advantage in active layer volume. It is envisaged that these study outcomes will provide important guidelines in the design of HSS OPV cells.Article Machine Learning for V2X-Enabled Microgrids: A Bibliometric and Thematic Review of Intelligent Energy Management Applications(Springer Heidelberg, 2026-03-09) Dogan, Yasemin; Unlu, RamazanModern power systems are evolving due to convergence of electric mobility, artificial intelligence, and renewable energy integration. Electric vehicles serve as dynamic, mobile energy storage units playing a vital role in ensuring resilient microgrid operations, via vehicle-to-everything (V2X) technology. However, despite the rise of machine learning (ML) in energy management, much of the existing literature remains fragmented lacking a holistic perspective across all facets of V2X-enabled microgrids. This study fills this gap by conducting a systematic bibliometric and thematic analysis of 310 articles obtained from Web of Science (2013-2024). By combining bibliometric mapping with thematic synthesis, the research identifies dominant and emerging ML techniques-ranging from reinforcement learning to federated learning-and evaluates their roles in microgrid management. The study highlights underexplored areas, including decentralized coordination, encouraging prosumer participation, understanding user behavior, safeguarding cybersecurity, improving real-time optimization, and the effective integration and adaptation of V2X technology within microgrid ecosystems. These gaps emphasize the need for interdisciplinary research and policy frameworks to address the social dimensions of future energy systems. Beyond a comprehensive overview, this paper proposes a research roadmap integrating technical, social, and policy dimensions. It offers actionable guidance for researchers, stakeholders aiming to unlock the potential of intelligent, human-centered, and socially inclusive energy ecosystems. Furthermore, the findings align with UN Sustainable Development Goals (SDG 7, 11, and 13), while also creating a positive impact on humanity by supporting the well-being of both society and the planet. Ultimately, this reinforces the indispensable role of ML in advancing the zero-carbon transition.Book Part A Systematic Review of Optimization Studies Used in Renewable Energy Systems(Springer Science and Business Media Deutschland GmbH, 2026) Söylemez, İ.; Erdoğan, A.This study presents a literature review of recent studies on renewable energy systems. Due to the large number of studies, this study has been limited to some keywords. When only the word “renewable energy systems” is searched, there are more than 14,343 studies in the literature between 2017 and 2024. A systematic search was conducted for the studies in which “optimization” or “mathematical model” was mentioned as a solution methodology. A total of 755 studies were identified in the “Scopus database” and analyzed for these studies. A detailed examination was carried out for the type of studies (research article, review, conference paper, etc.), countries where the studies were carried out, authors who carried out the studies and their statistics with each other, and so on. With this study, an overview of the literature will be provided and it will be a guiding study for researchers on the direction of the studies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Article Modeling and Simulation of Dynamic Energy Management Systems for Smart Buildings(TÜBİTAK, 2025-11-25) Ozel, O.; Rıfat Boynueğrİ, A.; Yigit, H.; Tekgun, B.; Boynuegri, Ali RifatThis study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both natural gas and electricity consumption, leading to substantial cost savings. Specifically, the proposed system reduced natural gas consumption by 3.79% and electricity consumption by 35.62%, highlighting its potential to enhance energy efficiency and sustainability in residential settings. © This work is licensed under a Creative Commons Attribution 4.0 International License.Article Citation - Scopus: 46Willingness to Pay for Renewable Electricity: A Contingent Valuation Study in Turkey(Elsevier Inc., 2019-12) Dogan, Eyup; Muhammad, IftikharRenewable energy sources are advised as an important alternative vehicle for dealing with a high rate of energy dependency and global warming. Turkey has also an ambitious national energy goal of minimizing energy import and producing 30% of electricity from renewable energy sources by 2023. However, it may not be easy to reach these goals. Willingness to Pay (WTP) thus plays a central role in directing appropriate policies for the country to realize its energy targets. This study reviews previous studies in the same literature as well as examines WTP of Turkish citizens for renewable electricity energy by using a stratified-sample and contingent valuation survey of 2500 households. The results from estimated models show that environmental conscience, membership to an environmental organization, age, education level, gender and income of households are significant determinants of WTP. In addition, the mean value of WTP for green electricity by Turkish households is estimated at around US$ 1 (with the exchange rate 5,3 TL/ US$) per month per household. A number of policy suggestions are further discussed. © 2023 Elsevier B.V., All rights reserved.Article Citation - WoS: 20Citation - Scopus: 22Multi-Objective Turbine Allocation on a Wind Farm Site(Elsevier Sci Ltd, 2024-02) Dincer, A. E.; Demir, A.; Yilmaz, K.The Multi-Objective Turbine Allocation (MOTA) method is introduced as a novel approach for wind farm layout optimization and site selection. By incorporating Geographic Information System (GIS) tools and the Analytical Hierarchy Process (AHP), the MOTA method offers a comprehensive solution to balance energy production, cost factors, and environmental impacts. In this study, the MOTA method is applied to Go center dot kceada, Turkiye, for wind farm development. Results show that the MOTA method effectively proposes the optimum wind farm layout by selecting the best site for each turbine. The sequential turbine allocation approach, integration of multiple objectives, and use of GIS tools and AHP are the key capabilities and novelties of the MOTA method. The method allows for flexible investment decisions, considering technical and economic aspects. The outcomes from the Go center dot kceada case study highlight the effectiveness of the MOTA method in maximizing energy production while considering cost factors and environmental impacts. The results indicate that for the selected objective functions, the optimal net profit is attained with the installation of 155 turbines on Go center dot kceada. The MOTA method presents a practical and efficient solution for wind farm development, contributing to sustainable and efficient renewable energy generation.Conference Object In-Pipe Electrical Machine Design for Smart Clean Water Grid Monitoring and Control Stations(IEEE, 2025-06-11) Erkan, Murat; Boynuegri, Ali Rifat; Tekgun, BurakThis study presents the design of an electric machine intended to supply the electrical energy required for the operation of electronic devices and mechanical equipment that form part of a clean water smart grid network powered by renewable energy sources. The proposed machine is a permanent magnet synchronous generator (PMSG), specifically designed to operate under realistic physical and hydraulic conditions within clean water distribution infrastructure. The in-pipe turbine responsible for driving the rotor of the generator was selected based on findings from a symposium paper identified through a comprehensive literature review. The daily energy requirements of the smart grid's electronic and industrial mechanical components were both theoretically estimated and experimentally validated, leading to the selection of a suitable energy storage unit. Pressure data from the clean water distribution line located on the street of the design office was measured and recorded at one second intervals over a 24-hour period. Using this dataset, the optimal hydraulic conditions and time frame for battery charging were identified from the pressure-time profile. A representative duty cycle was then defined, and the performance analysis of the in-pipe permanent magnet synchronous generator was carried out accordingly.Conference Object Citation - Scopus: 1Hybrid Renewable Energy to Greener and Smarter Cities: A Case Study of Kayseri Province(Springer Science and Business Media Deutschland GmbH, 2024) Bekçi, Eyüp; Koca, KemalIn this study, a hybrid energy system was implemented to fulfill the electricity requirements of the trams operating in Kayseri province. The tram's annual electricity consumption data was acquired on a monthly basis from the local electricity company in Kayseri. Utilizing the obtained data, energy and cost simulations were conducted employing the Homer-Pro program. The primary objective of this investigation is to enhance sustainability while satisfying electricity demands with minimal carbon emissions. Consequently, the established hybrid energy system incorporates renewable energy sources, specifically wind, solar, and biomass energy, with the inclusion of batteries for energy storage. Furthermore, generators and converters are integrated for energy conversion purposes. The study encompasses a detailed cost analysis to identify the most economically efficient hybrid energy system, determined through optimization studies. Through this research, it is anticipated that the implementation of such a system will significantly diminish carbon emissions in Kayseri, contributing to a substantial increase in sustainability. © 2024 Elsevier B.V., All rights reserved.Article Citation - WoS: 12Citation - Scopus: 16CO2 Emissions, Real GDP, Renewable Energy and Tourism: Evidence From Panel of the Most-Visited Countries(Cesky Statistical office, 2017) Dogan, EyupPrevious studies on the energy-environment-growth literature overlook the investigation of the most-visited countries. Since these countries do not only belong to the largest economies and the top carbon dioxide (CO2) emitters in the world but are also listed in renewable energy country attractiveness index, this study analyzes the impacts of real GDP, renewable energy and tourism on the level of CO2 emissions for the top 10 most-visited countries. Applying several panel econometric approaches, we find out that renewable energy mitigates the pollution whereas real GDP and tourism contribute to the level of emissions. Thus, regulatory policies are necessary to increase the awareness of sustainable tourism. In addition, the use of renewable energy and the adoption of clean technologies in tourism sector as well as in producing goods and services play a significant role in CO2 mitigation.