Browsing by Author "Dincer, A. E."

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Enhanced Objectivity of AHP for More Reliable Solar Farm Site Selection
(Wiley, 2025) Dincer, A. E.; Demir, A.; Yilmaz, K.
The analytic hierarchy process (AHP) is a popular decision-making method for reliable decisions in different areas of study. Although the conventional AHP method mathematically ensures the consistency of results, the reliability of these results depends on the expert manifests. While AHP was originally proposed for subjectively relatable criteria, there may also be additional objectively relatable criteria or a consensus about the final relation of some couple of criteria. To address these objective relations and/or consensuses, this study proposes the analytic hierarchy process with optimized hierarchy (AHP-OH). This method enhances the reliability of results by satisfying objective relations and/or consensuses about relations between criteria. The AHP-OH methodology was applied to select optimal photovoltaic (PV) farm locations in Konya Province, Turkey, a region characterized by diverse terrain and solar radiation levels. The study incorporated geographic information systems to analyze criteria, such as solar radiation rate, land use, slope, proximity to roads and transmission lines, and restricted areas. Results demonstrated that 2.56% of Konya's terrain is highly (80%-100%) suitable and 19.34% of it has moderately high (60%-80%) suitability for PV farm development, with five highly suitable regions identified. Notably, the locations of existing PV farms aligned closely with the identified suitable zones, validating the efficacy of the AHP-OH approach. This research underscores the importance of objectivity of decision-making methods and proposes AHP-OH to enhance the objectivity of the conventional AHP method. By providing a systematic and objective framework for spatial decision support systems, AHP-OH offers significant advancements for policymakers and developers in the renewable energy sector. Future applications of this methodology can extend to other regions and renewable energy sources, contributing to global efforts in sustainable energy development.
Citation - WoS: 17
Citation - Scopus: 17
Efficient Disaster Waste Management: Identifying Suitable Temporary Sites Using an Emission-Aware Approach After the Kahramanmaras Earthquakes
(Springer, 2023) Demir, A.; Dincer, A. E.
The clean and sustainable disposal of waste generated by natural disasters is crucial for effective disaster waste management. The initial stages of waste management involve determining the quantity of waste and identifying suitable temporary sites for its disposal. This study estimates that the Kahramanmaras province produced approximately 15 million tons of construction and demolition waste and 41,000 tons of household waste following the recent Kahramanmaras Earthquakes on February 6, 2023. Additionally, the study proposes eight temporary disaster waste sites considering various environmental and technical criteria. It should be noted that this is the first study to factor in emissions from waste transportation when selecting temporary disaster waste sites. An algorithm that considers the transportation network to calculate emissions for each map pixel is developed and integrated with geographic information system to identify the best temporary disaster sites. The results show that the most suitable location for temporary sites is southeast of the city center. The transportation time of the waste to the most suitable temporary site is found to be 98 days when 1000 trucks are in operation. The estimated emissions due to the transportation of the waste to the recycling facilities in this region are approximately 88,000 tons of carbon dioxide, 4.4 tons of sulphur oxide, 7.6 tons of nitrogen oxide, and 47.7 tons of particulate matter. The approach employed in this study can be utilized to identify suitable temporary sites for waste management after any natural disaster.
Citation - WoS: 17
Citation - Scopus: 19
Multi-Objective Turbine Allocation on a Wind Farm Site
(Elsevier Sci Ltd, 2024) 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.