Energy efficiency evaluation in ethylene production process with respect to operation classification. (1st January 2017)

• Record Type: Journal Article
• Authors: Gong, Shixin; Shao, Cheng; Zhu, Li
• Is Part Of: Energy. Volume 118(2017)
• Page Start: 1370
• Page End: 1379
• Publication Date: 2017-01-01
• Subjects: Energy efficiency evaluation -- DEA -- K-means -- Operation classification -- Ethylene production; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.11.012
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: 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. Highlights: DEA based on multi-working conditions is proposed to evaluate energy efficiency. Ethylene data is classified by k-means based on typical working conditions. Typical working conditions are conformed by feedstock and cracking depth. Dynamic energy efficiency evaluation is realized to offer the energy-saving advice. Results with practical ethylene data validate the availability of the proposed method.