Prioritization of sludge-to-energy technologies under multi-data condition based on multi-criteria decision-making analysis

Abstract

Aiming at promoting the sustainable development of sludge-to-energy and determining the decision-making process for the most sustainable option among all the scenarios, a novel multi-criteria decision-making method based on Dempster-Shafer (DS) theory and fuzzy best-worst method (FBWM) was developed. Four sludge-to-electricity technologies under uncertainty were prioritized, including incineration for electricity production, biogas from sludge digestion for electricity generation by fuel cells and gas engine, and microbial fuel cells (MFCs) for sludge treatment with electricity production. Four aspects and thirteen criteria were considered in the assessment and fuzzy BWM was employed to decide the fuzzy weights of these indicators. The uncertainty was resulted from different information forms, including crisp numbers, interval numbers and linguistic terms. Incomplete information also occurred in the data of MFCs. The results showed that incineration had the highest priority considering the overall performance on the selected indictors while MFCs had the worst performance due to the limited maturity of the technology. Biogas combustion for electricity production was also an acceptable option with stable market demand. The results also indicated the feasibility of using DS-FBWM for the multi-criteria decision-making problems of sludge-to-energy technologies with incomplete information and multi-data conditions, which can provide decision-making reference for stakeholders to make suitable choices according to the actual needs and preferences.