Energy efficiency assessment and resource optimization using novel DEA model: evidence from complex chemical processes
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ORIGINAL ARTICLE
Energy efficiency assessment and resource optimization using novel DEA model: evidence from complex chemical processes Kai Chen & Shuang Liu & Yongming Han & Yang Zhang & Zhiqiang Geng & Lin Liu & Tao Peng & Yifan Ding Received: 28 August 2019 / Accepted: 11 August 2020 # Springer Nature B.V. 2020
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 decisionmaking units (DMUs) better. Therefore, this paper Kai Chen and Shuang Liu contributed equally to this work. Kai Chen and Shuang Liu contributed to the work equally and should be regarded as co-first authors. K. Chen Guizhou Academy of Science, Guiyang 550001, China S. Liu : Y. Han (*) : Z. Geng (*) College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China e-mail: [email protected] e-mail: [email protected]
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.
Y. Zhang Sichuan Technology and Business University, Chengdu 611745, China
Keywords Energy efficiency assessment . Resource allocation optimization . Data envelopment analysis . Cosine similarity . Complex chemical processes
L. Liu College of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Introduction
T. Peng Bionic Sensing and Intelligence Center (BSIC), Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China Y. Ding BoHuaXinZhi Technology, Inc., Beijing, China
In 2019, China’s gross domestic product (GDP) output is more than $14 trillion, ranking second in the world (Michael 2020), to which complex industrial processes have contributed a lot. At the same time, industrial processes also consume large amounts of energy and release many greenhouse gases, such as carbon dioxide
Energy Efficiency
(CO2) (Xia et al. 2020). The global carbon emissions in 2019 a
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