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• W4312203942 endingPage "135481" @default.
• W4312203942 startingPage "135481" @default.
• W4312203942 abstract "Iran's energy consumption is constantly and rapidly increasing. Due to the country's geographical placement on the Sun Belt of the Earth, there is a great potential for photovoltaic (PV) energy to be used; however, it necessitates an evidence-based selection of appropriate locations to develop solar farms. In this paper, we used a new approach to prioritize potential PV plant sites employing geographical information system (GIS)-based Fermatean Fuzzy (FF) TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). We considered economic, geographic, climatic, infrastructures, and demographic criteria in GIS-based FF-TOPSIS and compared outputs with earlier versions of the TOPSIS method (crisp and triangular fuzzy numbers (TFN)). Although all three versions indicated high correlations of >0.89, 20.88% of pixels' priority differed depending on the chosen method's logic. Regarding the sensitivity analysis, the GIS-based FF-TOPSIS in terms of criteria's weight was substantially more resistant to uncertainty than the TNF-TOPSIS. Besides, the GIS-based FF-TOPSIS has rational sensitivity (i.e., tolerance) to the accuracy of input data. The GIS-based FF-TOPSIS method demonstrated sensitivity or robustness depending on the degree of uncertainty in the numbers, which can be altered depending on the expertise and mastery of experts. Our findings indicated that approximately 13.81% of the entire country has the potential for solar power plants. According to the results of the GIS-based FF-TOPSIS approach, the provinces of Sistan and Baluchestan, Hormozgan, Fars, and Khuzestan have the largest potential for solar power farms in Iran." @default.
• W4312203942 created "2023-01-04" @default.
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• W4312203942 date "2023-01-01" @default.
• W4312203942 modified "2023-09-30" @default.
• W4312203942 title "Evaluation of potential sites in Iran to localize solar farms using a GIS-based Fermatean Fuzzy TOPSIS" @default.
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• W4312203942 doi "https://doi.org/10.1016/j.jclepro.2022.135481" @default.
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