Solving renewable energy source selection problems using a q-rung orthopair fuzzy-based integrated decision-making approach. (10th January 2021)

• Record Type: Journal Article
• Authors: Krishankumar, R.; Nimmagadda, S. Supraja; Rani, Pratibha; Mishra, Arunodaya Raj; Ravichandran, K.S.; Gandomi, Amir H.
• Is Part Of: Journal of cleaner production. Volume 279(2021)
• Publication Date: 2021-01-10
• Subjects: Gini index -- Muirhead mean -- q-rung orthopair fuzzy set -- Renewable energy -- TODIM method -- MADM; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.123329
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: This paper proposes an integrated decision-making framework for the systematic selection of a renewable energy source (RES) from a set of RESs based on sustainability attributes. A real case study of RES selection in Karnataka, India, using the framework is demonstrated, and the results are compared with state-of-the-art methods. The main reason for developing this framework is to handle uncertainty and vagueness effectively by reducing human intervention. Systematic selection of RESs also reduces inaccuracies and promotes rational decision-making. In this paper, q-rung orthopair fuzzy information is adopted to minimize subjective randomness by providing a flexible and generalized preference style. Further, the study found systematic approaches for imputing missing values, calculating attributes' and decision-makers' weights, aggregation or preferences, and prioritizing RESs, which are integrated into the framework. . Comparing the proposed framework with state-of-the-art-methods shows that (i) biomass and solar are suitable RESs for the process under consideration in Karnataka, (ii) the proposed framework is consistent with state-of-the-art methods, (iii) the proposed framework is sufficiently stable even after weights of attributes and decision makers are altered, and (iv) the proposed framework produces broad and sensible rank values for efficient backup management. These results validate the significance of the proposed framework. Highlights of the work: Missing values are imputed systematically in decision matrices. Hesitation of decision makers is captured during attribute weight calculation. Decision makers' weights are calculated rationally for aggregation. Preferences are aggregated by capturing interdependencies among decision makers. q-rung orthopair fuzzy TODIM is proposed for renewable energy evaluation.