Energy efficiency assessment and resource optimization using novel DEA model: evidence from complex chemical processes

Abstract

Energy efficiency assessment and resource allocation optimization are conducive to improve the production and reduce carbon emissions in complex chemical processes. And the traditional energy efficiency assessment method based on data envelopment analysis (DEA) does not distinguish the effective decision-making units (DMUs) better. Therefore, this paper proposed a novel DEA method combining the cosine similarity (CS) (DEA-CS) to estimate the energy efficiency and optimize the resource of complex chemical plants. The ineffective and effective DMUs can be obtained by the DEA. Then, the CS can further distinguish the effective DMUs to obtain the optimal DMU, which makes the DEA model have the better discriminating ability. Moreover, through the input and output of the optimal DMU, the resource of ineffective DMUs can be optimized. Finally, the proposed model is used in energy efficiency assessment and resource optimization of ethylene and purified terephthalic acid (PTA) production plants in complex chemical processes. The experiments show that the energy-saving potential of ethylene and PTA production plants is improved by about 13.61% and 1.22%, respectively. Meanwhile, the average carbon emission–saving potential of the ethylene production plants is reduced by 12.58%, approximately.