Assessing the sustainable energy storage technologies using single-valued neutrosophic decision-making framework with divergence measure

Abstract

Energy storage technologies (ESTs) facilitate to handle intermittency of energy resources by storage surplus energy to utilize when it is required. Due to influence of numerous quantitative and qualitative attributes, evaluation of ESTs can be treated as a critical and vague multi-attribute decision-making (MADM) problem. As a type of neutrosophic set, single-valued neutrosophic set (SVNS) has been proven as one of the valuable and flexible ways to handle the imprecise, indeterminate and inconsistent information arises in real applications. Considering the uncertainty in ESTs selection process, this paper aims to propose an integrated MADM methodology by combining the MEthod based on the Removal Effects of Criteria (MEREC) and Evaluation based on Distance from Average Solution (EDAS) techniques with SVNSs. In this methodology, the score function and divergence measure-based procedure is proposed to derive the decision experts’ weights. In this respect, an innovative single-valued neutrosophic (SVN)-divergence measure is introduced with its desirable characteristics. Furthermore, the MEREC technique is extended under SVNS context to determine objective weights of the attributes. Later, an extended EDAS technique is introduced with the combination of SVN-divergence measure and MEREC model to assess and prioritize the alternatives under SVNS environment. To confirm the capability of introduced MADM methodology, a case study of ESTs selection is presented within the context of SVNS. Moreover, the merits of the proposed framework in terms of flexibility and robustness are shown by comparative analysis. Finally, the sensitivity analysis proves the stability of our obtained results.