Sustainability assessment of power generation systems under the objective consideration of criteria interactions.

The combination with carbon capture and storage (CCS) can significantly reduce CO 2 emission in power generation systems, however, it remains to be clarified whether the CCS combination can make the power generation systems more sustainable by comprehensively taking account of economic, social and environmental effects. In this study, a novel multi-criteria decision-making (MCDM) mathematical framework was developed to evaluate the sustainability of power generation systems using either fossil energy (with or without CCS) or renewable energy sources. In the mathematical framework, interval numbers are used to retain the objective uncertainties, and an improved Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) method is employed to determine the weights of the evaluation criteria, which can avoid subjective uncertainties while considering the interactions between evaluation criteria. According to the affecting factors calculated by G-DEMATEL, the interaction between criteria can be visualized and key criteria can be identified more intuitively. Finally, the interval Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR) method is employed to rank the sustainability of alternative power generation systems. In order to verify the developed framework, the sustainability of 6 power generation systems was assessed and compared by considering 10 criteria from dimensions of technology, environment, economy and society. The results show that "Wind power" is assessed as the most sustainable technology and the criterion of "Global warming" has the greatest impact on the sustainability of power generation systems, while the sustainability of power generation systems using fossil energy can be significantly improved by combining with CCS. • A framework for assessing the sustainability of power generation systems is proposed. • The effect of combining with carbon capture and storage is investigated. • An objective weighting method that consider the interaction of criteria is developed. • An approach is developed for visualizing the interaction between the criteria. [ABSTRACT FROM AUTHOR]