Abstract
The assessment target of energy consumption for ethylene equipment is based on Special Energy consumption (SEC) index currently without considering the differences among the raw materials, process technology and equipment scales. Because the standards of the traditional energy consumption statistical methods are not uniform, it affects the comparability of energy consumption. Aiming at the lack of energy consumption evaluation methods for existing ethylene industrial equipments, the data fusion method is researched to obtain the energy consumption indexes of the ethylene industrial devices. The data variance fusion method of multivariate series is proposed based on cluster analysis and variance analysis, and then consumption indexes about water, steam, electricity, fuel and virtual benchmark of SEC are extracted respectively in ethylene industrial process. It can objectively evaluate the energy consumption status of the ethylene equipments, analyze the actions and opportunities of energy saving, and then suggest the direction of the energy saving and the consumption reduction of ethylene equipments.
This work is partly supported by “the fundamental research funds for the central universities” (JD0906).
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Geng, Z., Han, Y., Zhang, Y., Shi, X. (2010). Data Fusion-Based Extraction Method of Energy Consumption Index for the Ethylene Industry. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_10
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DOI: https://doi.org/10.1007/978-3-642-15597-0_10
Publisher Name: Springer, Berlin, Heidelberg
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