Wind farm site selection using geographic information system and fuzzy decision making model
Выбор местоположения ветропарка с использованием географической информационной системы и нечёткой модели принятия решений
2024-07-14
SCID: 54.1/njgnr65s
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F-MARCOSF-SWARAfuzzy MCDMgeographic information systemwind farm site selection
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Abstract (AI)
As the demand for renewable energy sources increases, finding the right places to install wind turbines becomes more and more important. The goal of this research is to create and implement a technique that uses geographic information system (GIS) technology to discover appropriate wind farm locations utilizing multi-criteria decision-making (MCDM) approaches. The complexity of this decision-making process, which includes multiple criteria and uncertainty, requires the use of advanced techniques. Fuzzy MCDM methods provide a framework for evaluating and prioritizing potential wind farm sites, taking into account subjective judgments and linguistic terms. In this article, Fuzzy Stepwise Weight Evaluation Ratio Analysis (F-SWARA) is preferred for prioritizing and ranking the criteria in the wind farm installation, while Fuzzy Measurement Alternatives and Ranking by Compromise Solution (F-MARCOS) are used to determine the most suitable location for the wind farm. A database of alternatives and criteria was created using GIS, which was converted into a fuzzy decision matrix via triangular fuzzy numbers. In order to make this evaluation, Sivas province, located in the middle of Turkey, was chosen as the study area. Results obtained show that 36,5% of the whole study area is very suitable for wind farm, and Gürün and Kangal districts are suitable for wind farm. According to the result of F-SWARA method used to evaluate the criteria, wind speed is the most important criteria with a weight of 0,45039. According to the F-MARCOS method used for wind farm site selection, Ulaş district was determined the most suitable location. Furthermore, a sensitivity analysis was performed to test the robustness of the proposed methodology and the results revealed that the proposed integrated MCDM framework is feasible.
Key Findings
1
Fuzzy SWARA prioritizes wind speed as the most important criterion, assigning it a weight of 0.45039.
2
Gürün and Kangal districts are identified as suitable areas, while Ulaş district is ranked the most suitable location by F-MARCOS.
3
In Sivas Province, Turkey, 36.5% of the study area is classified as very suitable for wind farm development.
4
Sensitivity analysis indicates that the integrated GIS–fuzzy MCDM framework produces feasible and robust site-selection results.
5
The study integrates GIS with fuzzy multi-criteria decision-making to identify and rank suitable wind farm locations under uncertainty.
Research Object
Potential wind farm installation sites in Sivas Province, Turkey
Research Subject
Suitability ranking and spatial prioritization of wind farm sites based on multiple criteria under uncertainty
Publication Details
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2024-07-14
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