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


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.

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Data envelopment analysis


Cosine similarity


Data envelopment analysis combining cosine similarity


Decision-making units


Purified terephthalic acid


Gross domestic product

CO2 :

Carbon dioxide


Index decomposition analysis


Stochastic frontier approach


Affinity propagation


Slack-based measure


Analytic hierarchy process


Principal component analysis


Self-organizing cosine similarity learning network


Multi-verse optimization

d r :

Input vector of the rth DMU

e r :

Output vector of the rth DMU

v :

Weight coefficients of the pth input

u :

Weight coefficients of the qth output

η :

The effective value of input associated with the output


The optimal solution


Non-Archimedes infinitesimal

\( {g}_t^{-} \) :

Redundancy of pth input

\( {g}_t^{+} \) :

Deficiency of qth output

e t :

Unit vector

a · b :

The dot product of the two vectors


The modulo of vector A

cosθ :

Cosine of two vectors


GJ/ton ethylene




Acetic acid


The top of the solvent dehydration tower


Fuzzy artificial neural network


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This work is partly funded by the National Natural Science Foundation of China (21978013), the Fundamental Research Funds for the Central Universities (XK1802-4), the Science and Technology Major Project of Guizhou Province (Guizhou Branch [2018]3002), the Shenzhen Fundamental Research Program (JCYJ20170413164102261), and the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2016ZT06D631).

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Correspondence to Yongming Han or Zhiqiang Geng.

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Kai Chen and Shuang Liu contributed to the work equally and should be regarded as co-first authors.

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Chen, K., Liu, S., Han, Y. et al. Energy efficiency assessment and resource optimization using novel DEA model: evidence from complex chemical processes. Energy Efficiency 13, 1427–1439 (2020).

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  • Energy efficiency assessment
  • Resource allocation optimization
  • Data envelopment analysis
  • Cosine similarity
  • Complex chemical processes