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首页> 外文期刊>Journal of Cleaner Production >A novel data envelopment analysis cross-model integrating interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling: Application to ethylene industries
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A novel data envelopment analysis cross-model integrating interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling: Application to ethylene industries

机译:结合解释性结构模型和层次分析法的能效评估和优化模型的新型数据包络分析交叉模型:在乙烯工业中的应用

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摘要

Energy efficiency analysis and production efficiency improvement are effective ways to promote the sustainable and stable development of ethylene industries. Therefore, this paper proposes novel data envelopment analysis cross-model integrated interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling. The interpretative structural model integrating analytic hierarchy process is used to fuse the multidimensional production data to reduce the dimension and obtain comprehensive evaluation indicators, thus reducing the multidimensional indicators influence on the data envelopment analysis model. Then these several fusion results are used as the input indicators of the improved data envelopment analysis cross-model. And the ethylene yield is used as the output index to build the energy efficiency evaluation and optimization model of ethylene production plants. Finally, according to cross-efficiency values and slack variables, the energy efficiency levels of ethylene plants in each month and year are analyzed. The experimental results show that the distinction of the efficiency values is more obvious and accurate. Moreover, the proposed method can optimize production efficiency and improve the proportion of the efficiency value greater than 0.8 increased by 66.6% of ineffective production plants. (C) 2019 Elsevier Ltd. All rights reserved.
机译:能源效率分析和生产效率提高是促进乙烯工业可持续稳定发展的有效途径。因此,本文提出了新颖的数据包络分析跨模型集成解释结构模型和层次分析法,用于能效评估和优化建模。解释性结构模型集成了层次分析法,用于融合多维生产数据以减少维度并获得综合评价指标,从而减少多维指标对数据包络分析模型的影响。然后,将这几个融合结果用作改进的数据包络分析交叉模型的输入指标。并以乙烯收率为生产指标,建立了乙烯生产装置的能效评价和优化模型。最后,根据交叉效率值和松弛变量,分析了乙烯装置每月和每年的能效水平。实验结果表明,效率值的区别更加明显和准确。而且,所提出的方法可以优化生产效率,提高效率值的比例,将大于0.8的无效生产工厂的效率提高66.6%。 (C)2019 Elsevier Ltd.保留所有权利。

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