A granular multicriteria group decision making for renewable energy planning problems

In this study, we introduce and develop a novel decision-making model that provides an original solution to problems of renewable energy site planning. The main idea is to construct a comprehensive and systematic methodology of ranking alternatives encountered in the environment of multicriteria group decision making. The proposed framework is systematically structured with the aid of information granules, in particular, intervals and fuzzy sets. An overall architecture is developed in a comprehensive manner. The inherent facet of uncertainty, it is formalized and processed with the aid of information granules. The two main design phases involve the determination of preference degrees of alternatives with respect to the set of criteria and the weights of the corresponding criteria. The underlying estimation process is realized with the use of the pairwise comparison method (analytical hierarchy process-AHP) resulting in information granules (fuzzy sets) quantifying degrees of preference and relevance of the weights. In light of the group nature of the decision process and diversity of views and opinions conveyed by the individual decision-makers, the results provided by them are aggregated and the diversity (variability) in the individual assessments is captured through information granules of type-2. Finally, a variety of ranking procedures is analyzed and carefully assessed. A case study of selection of solar site is provided to demonstrate the usefulness of the developed approach. Compared with the existing decision-making scenarios, we show that the new model exhibits a significant level of reliability and is characterized by better interpretability.

Automated summary

In this study, a novel decision-making model is introduced and developed to address the problems of renewable energy site planning. The model utilizes information granules, specifically intervals and fuzzy sets, to construct a comprehensive and systematic methodology for ranking alternatives in a multicriteria group decision-making environment. By formalizing and processing uncertainty through information granules and considering the diversity of individual decision-makers' views and opinions, the model provides a reliable and interpretable solution. The usefulness of the model is demonstrated through a case study on solar site selection.