Journal
ENERGY
Volume 203, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.117893
Keywords
Energy efficiency evaluation; Mechanism model; Data-driven; Domain knowledge; Complex petrochemical industry
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Funding
- National Natural Science Foundation of China [21978013, 61533003]
- Fundamental Research Funds for the Central Universities, China [XK1802-4]
- Science and Technology Major Project of Guizhou Province (Guizhou Branch) [[2018]3002]
- Industrial Internet Innovation and Development Project [TC19084DY]
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As the most effective indicator for energy saving and emission reduction, energy efficiency evaluation is widely used in complex petrochemical industries. It is nowadays common to combine traditional mechanism methods based on momentum transport, energy transport, quality transport (TT) and reaction engineering (RG) (TT-RG), with data-driven artificial intelligence methods. Using the combined method to achieve production optimization and energy saving by analyzing the evaluation indicator of energy efficiency has gradually become an important part in complex petrochemical industries. Therefore, this paper introduced the main methods and the latest research results of energy efficiency evaluation of complex petrochemical industries. These methods are mainly divided into three parts, including the mechanism methods based on TT-RG, the data-driven artificial intelligence methods, and the hybrid methods combining the mechanism and the data-driven. Then, different methods are compared and described in detail. Moreover, the best method for evaluating the energy efficiency can be found to provide theoretical guidance for energy saving and emission reduction of complex petrochemical industries. Finally, the future development direction for energy efficiency evaluation in complex petrochemical industries is given. (C) 2020 Elsevier Ltd. All rights reserved.
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