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Energy efficiency evaluation in ethylene production process with respect to operation classification

机译:关于生产分类的乙烯生产过程中的能效评估

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摘要

It is significant to increase energy efficiency of ethylene production process for petrochemical enterprise, in terms of the production level and productive benefits. But it is noticed from the actual production data that the energy efficiency of ethylene production has a strong relationship with the complex production conditions. It is necessary to combine the ethylene production states analysis with energy efficiency evaluation and improvement. With regard to the efficiency evaluation methods, data envelopment analysis (DEA) concentrate on a single working condition mode and fails to take into account the complicated working conditions. Therefore, a new energy efficiency evaluation method is presented with respect to operation classification. First, the typical working conditions of the ethylene production are determined corresponding to the key factors, including crude material composition and cracking depth, and the working conditions of production data are classified by k-means clustering algorithm. On the basis of the multiple working conditions, DEA is used to evaluate the performance of decision making units (DMUs) for different working conditions respectively. In addition, the advice on energy new allocation is suggested to the operators. Finally, the accuracy and effectiveness of the proposed method are illustrated by applying in a practical ethylene production. (C) 2016 Elsevier Ltd. All rights reserved.
机译:对于生产水平和生产效益而言,提高石化企业乙烯生产过程的能源效率具有重要意义。但是从实际生产数据中可以看出,乙烯生产的能源效率与复杂的生产条件有很强的关系。有必要将乙烯生产状态分析与能效评估和改进相结合。关于效率评估方法,数据包络分析(DEA)集中于单一工作条件模式,而没有考虑复杂的工作条件。因此,针对操作分类提出了一种新的能效评估方法。首先,根据关键因素确定了乙烯生产的典型工作条件,包括原料组成和裂解深度,并通过k-均值聚类算法对生产数据的工作条件进行了分类。在多种工作条件的基础上,DEA分别用于评估不同工作条件下决策单元(DMU)的性能。此外,还向运营商提出了有关能源新分配的建议。最后,通过在实际乙烯生产中的应用说明了所提方法的准确性和有效性。 (C)2016 Elsevier Ltd.保留所有权利。

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