3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Yayın Leveraging renewable energy for Türkiye's future hydrogen supply chain(Elsevier Ltd, 2025-09-09) Türkali Özbek, Busenur; Erdoğan, Ahmet; Güler, Mehmet GürayAs energy and climate crises necessitate a shift to sustainable resources, hydrogen - with its zero-emission potential-is expected to play a key role in the energy transition. Designing an effective hydrogen supply chain (HSC) is essential to realizing this potential. This study introduces a multi-period, multi-objective stochastic optimization model for Türkiye's transportation-sector HSC. It addresses gaps in existing research by integrating dynamic renewable energy availability, lifecycle-based CO2 emissions, and regional green hydrogen prioritization. The ε-constraint method is used to balance economic and environmental objectives. Results show that Türkiye can significantly reduce emissions by gradually transitioning from fossil-based production and by optimizing facility locations based on regional solar, wind, and hydrogen sulfide potential. Centralized production reduces costs but increases transport risk and emissions, while localized production improves resilience yet may increase fossil fuel reliance in resource-limited regions. These findings offer strategic guidance for aligning hydrogen planning with Türkiye's climate commitments.Yayın Leveraging renewable energy for Turkey's future hydrogen supply chain: a stochastic programming model(Dicle Üniversitesi, 2024-05-15) Türkali Özbek, Busenur; Erdoğan, Ahmet; Güler, Mehmet GürayFossil fuel dependence and rising CO2 emissions due to population growth and technological advancements necessitate a transition to clean energy sources. The transportation sector, a major contributor to CO2 emissions, requires alternative solutions like hydrogen fuel cell electric vehicles (HFCVs). However, widespread adoption hinges on a reliable hydrogen supply chain (HSC). This study aims to design a HSC for Turkey's transportation sector in 2050, considering potential renewable energy sources. A scenario-based stochastic programming approach is employed to address the uncertainty in demand. Additionally, the Epsilon Constraint Method is used to incorporate multiple objectives, including cost, CO2 emissions, and risk, into the model. The results show that the types of facilities opened are compatible with the renewable energy potential of each grid and there is a decentralized structure. This study contributes to the design of a sustainable HSC for Turkey, showcasing a methodology that can be adapted by other countries aiming to integrate renewable energy sources into their hydrogen supply chains.Yayın Analyzing the performance of different costBased methods for the corrective maintenance of a system in thermal power plants(World Academy of Science, Engineering and Technology (WASET), 2019-08-16) Özgür Ünlüakın, Demet; Türkali Özbek, Busenur; Aksezer, Sezgin ÇağlarSince the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.
