Optimizing decision making for sustainable solar thermal energy systems within an intuitionistic fuzzy environment

Abstract

 In the context of addressing global energy needs and climate
change, the transition to sustainable energy systems has become one of
the most important objectives, and in this context. Solar-thermal energy
systems are among the most important sources of renewable energy solu
tions. However, existing research on solar-thermal energy systems often
falls short in effectively handling uncertainty and the credibility of expert
evaluations, which are essential for ensuring reliable decision-making.
Traditional methods still focus on deterministic or simplified models, ne
glecting the intricate and uncertain evaluations present in real-world sit
uations. To address these shortcomings, this study employs intuitionistic
fuzzy credibility numbers (IFCNs), which explicitly incorporate member
ship, non-membership, and credibility degrees, enabling a more compre
hensive representation of uncertain and hesitant information. Based on
IFCNs, we introduce a new, more effective method of handling credibil
ity in aggregation named the generalized intuitionistic fuzzy credibility
numbers weighted averaging (GIFCNWA) operator. Based on this opera
tor, a multi-attribute decision-making algorithm is proposed that integrates
attribute importance and reliability of evaluations. The proposed method
ology is applied to a real-world decision-making problem in solar ther
mal energy storage by considering four options: nanostructured absorber
coatings, advanced phase-change materials, high-temperature alloys, and
adaptive control systems. The results identify nanostructured absorber
coatings as the most optimal solution. A parametric sensitivity analysis is
conducted, demonstrating the robustness and stability of the proposed op
erator under varying parameter conditions. A comparative analysis with existing decision-making techniques reveals the superiority and consis
tency of the proposed operator in delivering reliable results.