Multi-perspective evaluation of integrated active cooling systems using fuzzy decision making model

• Main Authors: Albahri O.S., Alamoodi A.H., Deveci M., Albahri A.S., Mahmoud M.A., Sharaf I.M., Coffman D.M.
• Other Authors: 57201013684
• Format: Article
• Published: Elsevier Ltd 2024
• Subjects: 2-Tuple linguistic pythagorean fuzzy sets; Climate change; FWZIC; Household energy consumption; Integrated active cooling systems; MABAC; Cooling; Cooling systems; Decision making; Energy utilization; Linguistics; Sensitivity analysis; Thermoelectric equipment; 2-tuple linguistic; 2-tuple linguistic pythagorean fuzzy set; Active cooling; Fuzzy Decision making; Integrated active cooling system; Multi-perspective; Performance criterion; climate change; cooling; decision making; energy use; fuzzy mathematics; household energy; multicriteria analysis

As global median temperatures continue to rise, the demand for active cooling systems (ACs) is increasing. These systems are particularly prevalent in developed countries for maintaining comfort during hot weather. Various ACs technologies are available, and assessing their performance in multi-perspective settings is necessary to determine the best option for intended usage. This requires an evaluation platform for assessment. This paper presents a novel multi-criteria decision-making (MCDM) model based on a new integrated 2-tuple linguistic Pythagorean fuzzy-weighted zero-inconsistency (2 TLP-FWZIC) and modified 2-tuple linguistic Pythagorean fuzzy multi-attributive border approximation area comparison (2TLPF-MABAC). The former is used to determine the importance of assessment criteria, while the latter is employed for selecting the optimal ACs using the obtained weights. The first-level weighting results reveal that performance criteria were predominantly favored for assessment, with �energy performance� acquiring the most significant weight (0.2487) among all performance criteria. In terms of ACs selection results, among the 20 tested and assessed systems, the �geothermal borehole electricity-based ACs� obtained the highest score value (0.1296), while the �window packaged electricity-based ACs� had the lowest score (-0.0515). The robustness of the results was confirmed through sensitivity analysis. � 2023 The Authors