4.7 Article Proceedings Paper

Characterisation of heavy petroleum fractions using modified molecular-type homologous series (MTHS) representation

期刊

ENERGY
卷 33, 期 6, 页码 974-987

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2007.11.006

关键词

refinery feedstock; characterisation; lumped species; molecular-type homologous series matrix; optimisation; pivot method

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The molecular characterisation of refinery feedstocks is a challenging task since, typically, a vast number of components are present in the mixture. Non-experimental approaches for characterisation of hydrocarbon streams fall into three categories: pseudo-component, compound class and average structural parameter methods. In this work, a new compound class approach is used to represent any hydrocarbon stream (with boiling range up 700 degrees C) via a modified molecular-type homologous series (MTHS) matrix. The fraction of each component/cut in the feedstock stream is estimated by minimising the discrepancies between the bulk physical properties and the ones reconstructed through our characterisation method. Mixture properties are calculated by applying Kay's mixing rule [Gases and vapors at high temperature and pressure-density of hydrocarbon. Ind Eng Chem 1936;28:1014-9], for each cut. The paraffinic, naphthenic and aromatic content of each cut of the analysed mixture can then be determined. To test the method, 15 olefin-free petroleum samples, from refineries all over the world, covering boiling ranges from 120 to 615 degrees C were characterised. The results show good agreement with the experimental data. A technique for integrating our characterisation approach with refinery lumped kinetic models is also presented. It is based on the pivot method [Kumar S, Ramkrishna D. On the solution of population balance equations by discretisation-I. A fixed pivot technique. Chem Eng Sci 1996;51:1311-32] appropriately modified to use the information provided by the characterisation procedure in order to obtain the necessary input for kinetic/reaction models, ensuring species mass conservation. (C) 2008 Elsevier Ltd. All rights reserved.

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