Sustainability prioritization of energy systems by developing an integrated decision support framework with hybrid-data consideration

Abstract

Rapid development in energy systems results in a choice question for decision-makers. Since many conflicting criteria are involved in the decision process, multi-criteria decision-making (MCDM) could be used. To make the decision process more suitable and reliable in reality, this paper introduces a sustainability prioritization framework with hybrid-data consideration via the integration of fuzzy group Delphi (FGD), fuzzy best-worst method (FBWM), and fuzzy best-worst projection (FBWP). In which, the triangular fuzzy number is incorporated into the framework to address the hybrid-data issues under uncertainty; the FGD rationally identifies the key criteria by implementing group consensus decisions, the FBWM accurately assigns the weights to the criteria by preserving the consistency in cognitive processes under uncertainty, and the FBWP rigorously ranks the alternatives by incorporating the absolute and relative performances regarding the multi-criteria. An illustrative case regarding ammonia production systems was studied, while the effectiveness and advantages of the framework were validated by results comparisons. In summary, this work makes methodological contributions to the sustainability prioritization of energy systems, including properly considering the uncertain hybrid data in decision-making, rationally selecting the key criteria and accurately determining their weights, and reliably ranking the alternative systems in the context of sustainability.