WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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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.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 - WoS: 190Citation - Scopus: 203The Role of Economic Policy Uncertainty in the Energy-Environment Nexus for China: Evidence From the Novel Dynamic Simulations Method(Academic Press Ltd- Elsevier Science Ltd, 2021-08) Amin, Azka; Dogan, EyupEven though a great number of researches have explored the determinants of carbon emissions, the impact of economic policy uncertainty (EPU) on the environment has not been fully investigated in the energy-environment literature. Since recent studies show a strong relationship between the external environment and uncertainty, the present study for the first time in the literature aims to explore the function of EPU in the energy-environment nexus for China by using the novel bounds testing with dynamic simulations. The empirical results indicate that increases in the real income and energy intensity contribute to environmental pollution while increases in renewable energy lower the level of emissions. Besides, an increase in EPU causes an increase in the volume of carbon emissions. As EPU increases, the government's attention to implement environmental protection policies decreases, and the execution of the environment-related strategies is likely directed in an expected way. The empirical findings suggest that the government should establish consistency in economic and environmental policies to mitigate environmental pollution and thus to reach environmental sustainability.Article Citation - WoS: 194Citation - Scopus: 217The Impact of Renewable Energy Consumption to Economic Growth: A Replication and Extension of Inglesi-Lotz (2016)(Elsevier, 2020-08) Dogan, Eyup; Altinoz, Buket; Madaleno, Mara; Taskin, DilvinThis study replicates and extends the results presented in a top-cited article in this journal, Inglesi-Lotz (2016), which analyzes the impact of renewable energy consumption to economic growth for the OECD countries by applying the ordinary least squares with fixed effect estimator on the data from 1990 to 2010. By using the same data and methods, this study first produces and compare empirical results with those reported in the original article. Then, it applies a set of new econometric methods on the same data to address heterogeneity in renewable energy and economic growth across the analyzed group of countries. The panel quantile regression estimation shows that the effect of renewable energy consumption on economic growth is positive for lower and lowmiddle quantiles; however, its effect becomes negative for middle, high-middle, and higher quantiles when renewable energy consumption is proxied by the absolute value. Furthermore, a negative impact of renewable energy on economic growth is observed in almost all quantiles when it is proxied by the share of renewable energy consumption to total energy consumption. These results greatly differ from those of the original study (C) 2020 Elsevier B.V. All rights reserved.Article Tapered Curved-Beam Hinges for Electret-Based Vibration Energy Harvesting Devices(IOP Publishing Ltd, 2024-12-01) Hah, DooyoungInterest in vibration energy harvesting have been growing recently for various applications. One of the major development goals for vibration energy harvesters has been improvement in energy conversion efficiency. To pursue that goal, one of the main approaches has been to broaden the spectra of harvesters. Employment of nonlinear springs, such as curved-beam hinges, has proven to be effective for that purpose. The main contribution of the current study is to introduce a lateral taper to the curved beam so as to further optimize the harvester performances. Via numerical analysis by using stochastic differential equations, the study shows that at 0.05g of vibration strength, tapered curved-beam hinges can result in higher electric power output than the non-tapered ones. Deformation-induced stress was taken into consideration as well, in reference to the fracture strength of the material (single-crystal silicon). At lower vibration strength (0.02g), spring nonlinearity becomes weaker, and as a result, the narrowest curved-beam hinge produces the highest output power. Overall, the current study demonstrates that tapering of the curved beam can be a useful addition in the vibration energy harvester design.Article Citation - WoS: 75Citation - Scopus: 89Revisiting the Nexus of Ecological Footprint, Unemployment, and Renewable and Non-Renewable Energy for South Asian Economies: Evidence From Novel Research Methods(Pergamon-Elsevier Science Ltd, 2022-07) Dogan, Eyup; Majeed, Muhammad Tariq; Luni, TaniaGiven the need to employ novel research methods in the energy-environment nexus, the objective of the present research is to investigate the impacts of real output, unemployment, and renewable and nonrenewable energy on ecological footprint under a STIRPAT theoretical framework by applying the second-generation unit root, cointegration, Granger-causality, and long-run estimation methods on the annual data from 1990 to 2017 for South Asian economies. Empirical results show that increases in unemployment and renewable energy decrease ecological footprint while increases in real income and non-renewable energy hurt the environment. This study confirms the adverse effect of renewable energy on environmental degradation as well as the trade-off between unemployment and pollution through multiple robustness and sensitivity checks. In addition, the causality test supports unidirectional causality from income, renewable energy, and non-renewable energy to ecological footprint. Regarding policy perspectives, the governments of the South Asian region should support the deployment of renewable energy through various channels and regulations. The development of technologies that promote sustainable production and consumption play critical roles for reducing the trade-off unemployment and ecological footprint. Further policy suggestions are discussed in the study.(c) 2022 Elsevier Ltd. 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 Citation - WoS: 1Citation - Scopus: 1Microgrid Environmental Impact(Institute of Electrical and Electronics Engineers Inc., 2020-09-28) Al-Agtash, Salem Y.; al-Hashem, Mohammad; Batarseh, Mohanad; Bintoudi, Angelina D.; Tsolakis, Apostolos Charalampos; Tzovaras, Dimitrios K.; Hadjidemetriou, Lenos; Khiat, MounirPower plants have bad impacts on the environment. One of these impacts is Carbon Dioxide (CO2) emission resulted from power plants that depend on fossil fuel, oil and natural gas. Renewable energy is considered as an important solution for this problem since it is classified as clean and environmentally friendly source of energy and helps reducing the dependency on conventional power plants. High renewable energy penetration into power systems is a big challenge that can be solved by deploying the concept of smart Micro-Grids. This paper presents a study on how much reduction of CO2 emission can be resulted from deploying smart micro-grid concept on a university campus, German Jordanian University (GJU) campus was taken as a pilot. The micro-grid is meant to operate according to an optimum resource scheduling framework that guarantee a minimum operational cost while achieving high local power availability. © 2020 Elsevier B.V., All rights reserved.Article Citation - WoS: 147Citation - Scopus: 159Investigating the Spillovers and Connectedness Between Green Finance and Renewable Energy Sources(Pergamon-Elsevier Science Ltd, 2022-09) Dogan, Eyup; Madaleno, Mara; Taskin, Dilvin; Tzeremes, PanayiotisAlthough a few studies have analyzed the nexus of renewable energy and green finance, the literature lacks the use of renewable energy by sources. The other major failure is that it uses only annual and small data. Therefore, this study investigates the connectedness and spillovers relationship between green finance and five types of renewable energy (biofuels, fuel cell, geothermal, solar, and wind) by applying the novel TVP-VAR method of Balcilar et al. [1] to the daily indexes from July 31, 2014, to Feb 4, 2022. The results show that dynamic connectedness, both total and pairwise, is heterogeneous over time and influenced by economic events. Furthermore, wind is found to be the largest transmitter of shocks to green finance, followed by biofuels, while both fuel cell and geothermal receive the least shocks. The findings suggest that green finance is mostly a net receiver of shocks from renewable energy sources and that wind has been a net receiver of shocks during the COVID-19 pandemic. A high interconnectedness between the indexes highlights the safe-haven property for diversification purposes of green finance. Our results are important for energy policymakers, those responsible for the implementation of environmental policies, individual investors, and portfolio managers, while also shedding light on the achievement of COP26 goals.