Assessment of renewable energy systems through the integrated SWARA-LOPCOW-EDAS decision-making method with a novel Fermatean fuzzy scoring function
提出一种新的Fermatean模糊多准则决策框架，通过专家调查评估五种可再生能源，发现太阳能和风能表现最佳，政策一致性和减排潜力是关键准则。
This study proposes a novel Fermatean fuzzy (FF) multi-criteria decision-making framework to evaluate renewable energy systems under uncertainty, focusing on sustainable development and efficient energy utilisation. The novelty lies in developing a new scoring function for FF sets that enhances the differentiation of closely ranked alternatives and in extending step-wise weight assessment ratio analysis and logarithmic percentage change-driven objective weighting methods into the FF domain for computing subjective and objective weights, respectively. The integrated framework employs the distance-based evaluation from average solution method to rank five renewable sources, solar, wind, hydro, biomass, and geothermal across four sustainability main criteria and eighteen sub-criteria. Data are collected through structured expert surveys involving professionals from the renewable energy sector. The analysis identifies policy alignment (weight: 0.09985) and emission reduction potential (weight: 0.07838) as the most influential criteria. Solar energy ranks highest with a performance score of 0.83208, followed by wind (0.65355), while biomass scores lowest (0.24781). Sensitivity and comparative analyses validate the robustness and consistency of the proposed model. The results suggest prioritising solar and wind energy and offer actionable insights for policymakers to develop resilient and uncertainty-aware renewable energy strategies.