WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11289

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Citation - WoS: 17
Citation - Scopus: 19
A Novel Procedure for the AHP Method for the Site Selection of Solar PV Farms
(Wiley-Hindawi, 2024) Abdullah Demir; A. Ersin Dinçer; Kutay Yılmaz; Yilmaz, Kutay; Demir, Abdullah; Dincer, A. Ersin
This study proposes a novel approach to enhance the analytic hierarchy process (AHP) for the selection of suitable sites for solar photovoltaic (PV) farms. This approach is particularly beneficial when it is possible to establish a predefined objective relation in the final weights of the AHP method. The methodology focuses on achieving this predefined relation introducing a systematic revision of the constants of related constraints. In this study the costs of constructing a unit transmission line and road in the Kayseri Province are objectively related and the initial constant matrix of the AHP method is iteratively revised until the relation of the final weights converges to the predefined one. The suitability of solar PV farm locations is classified into five classes revealing approximately 28% (40-100% of suitability) of the province as favorably suitable and designating about 67% as restricted zones. The findings reveal notable distinctions between the revised weights and those derived from the conventional AHP method. The disparity in weights for various constraints varies from 13.5% to 7.2%. Consequently the alterations in the area of suitability regions range from 3.4% to 50%. The revision of AHP weights results in a reduction in higher-suitability areas coupled with a significant expansion in the region exhibiting lower suitability. Notably the extent of change in the suitability map increases when the difference in ratios between two criteria obtained from the AHP and the predefined objective relation is high. The proposed method demonstrates its applicability in regions like Kayseri where an objective relation between criteria can be established. Given the inherent subjectivity of the AHP method the proposed procedure becomes essential to attain more objective weights. Since the methodology objectively adjusts weights based on known ratios it increases the accuracy and reliability of site selection studies. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 18
Citation - Scopus: 20
Effect of urbanization on surface runoff and performance of green roofs and permeable pavement for mitigating urban floods
(Springer Science and Business Media B.V., 2024) Şevki Ozturk; Kutay Yılmaz; A. Ersin Dinçer; Volkan Kalpakcı; Yilmaz, Kutay; Dincer, A. Ersin; Ozturk, Sevki; Kalpakci, Volkan
Floods are increasingly becoming a significant concern due to climate change global warming and excessive urbanization. The Intergovernmental Panel on Climate Change (IPCC) has projected that global warming will continue to contribute to more frequent and severe floods and hydrological extremes. In response to these challenges nature-based solutions (NBSs) have gained recognition as effective approaches to mitigate the adverse impacts of floods by focusing on ecosystem conservation restoration and sustainable utilization of natural resources. This study examines a flood that occurred in the Erkilet District of Kayseri Türkiye on September 22 2022 as a result of intense rainfall. It involves a thorough on-site investigation to assess the hydraulic hydrologic and geotechnical attributes of the study area. The findings from the field study indicate that the primary cause of the flood is attributed to excessive urbanization. To further analyze the impact of urbanization a hydraulic model is developed considering both the physical and topographical conditions of the study area for both the year 2006 and 2022. The simulation results reveal that the extent of inundation area and water depth has increased significantly due to the excessive urbanization that occurred within a 16-year period. Additionally the effectiveness of green roofs and permeable pavements as NBSs to mitigate urban flooding is explored. The implementation of green roofs and permeable pavements shows promising results reducing the adverse effects of urban floods by 3% to 8% depending on their specific locations and configurations. However the results suggest that NBSs alone cannot fully prevent floods so they should complement gray infrastructure. The novelty of the study lies in its ability to demonstrate the impact of urbanization and the effectiveness of nature-based solutions in mitigating flood extent based. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 18
Citation - Scopus: 20
Multi-objective turbine allocation on a wind farm site
(Elsevier Ltd, 2024) A. Ersin Dinçer; Abdullah Demir; Kutay Yılmaz; Yılmaz, K.; Demir, A.; Dinçer, A.E.
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 Gökçeada Türkiye 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 Gökçeada 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 Gökçeada. The MOTA method presents a practical and efficient solution for wind farm development contributing to sustainable and efficient renewable energy generation. © 2024 Elsevier B.V. All rights reserved.

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