Over the last decade, the total primary energy consumption has increased from 479 × 1015 BTU in 2010 to 528 × 1015 BTU in 2020. To address this ever-increasing energy demand, as well as prevent environmental pollution, clean energies are presented as a potential solution. In this regard, evaluating and selecting the most appropriate clean energy solution for a specific area is of particular importance. Therefore, in this study, a comparative analysis in Jiangsu province in China was performed by describing and implementing five prominent multi-criteria decision-making methods in the field of energy technology selection, including SAW, TOPSIS, ELECTRE, VIKOR, and COPRAS. The decision problem here consists of four clean energy options, including solar photovoltaic, wind, nuclear, and biomass, which have been evaluated by twelve basic and important criteria for ranking clean energy options. The obtained results, according to all five MCDM methods, indicate that solar photovoltaic was the optimal option in this study, followed by wind energy. The nuclear and biomass options placed third and fourth, respectively, except in the ELECTRE method ranking, in which both options scored the same and thus neither was superior. Finally, by conducting a comprehensive two-stage sensitivity analysis, in the first stage, it was found that changes in the weights of land use and water consumption criteria had the greatest impact on the performance of options, among which biomass and nuclear showed high sensitivity to variations in criteria weights. In the second stage, by defining five scenarios, the ranking of options was evaluated from different aspects so that the decision maker/organization would be able to make appropriate decisions in different situations.

In recent decades, there has been an increasing trend toward the technical development of efficient energy system assessment tools owing to the growing energy demand and subsequent greenhouse gas emissions. Accordingly, in this paper, a comprehensive emergy-based exergoeconomic (emergoeconomic) method has been developed to study the biomass combustion waste heat recovery organic Rankine cycle (BCWHR-ORC), taking into account thermodynamics, economics, and sustainability aspects. To this end, the system was formulated in Engineering Equation Solver (EES) software, and then the exergy, exergoeconomic, and emergoeconomic analyses were conducted accordingly. The exergy analysis results revealed that the evaporator unit with 55.05 kilowatts and the turbine with 89.57% had the highest exergy destruction rate and exergy efficiency, respectively. Based on the exergoeconomic analysis, the cost per exergy unit , and the cost rate of the output power of the system were calculated to be 24.13 USD/GJ and 14.19 USD/h, respectively. Next, by applying the emergoeconomic approach, the monetary emergy content of the system components and the flows were calculated to evaluate the system’s sustainability. Accordingly, the turbine was found to have the highest monetary emergy rate of capital investment, equal to , and an output power monetary emergy of . Finally, a sensitivity analysis was performed to investigate the system’s overall performance characteristics from an exergoeconomic perspective, regarding the changes in the transformation coefficients (specific monetary emergy).