General Information
    • ISSN: 2010-0221 (Print)
    • Abbreviated Title: Int. J. Chem. Eng. Appl.
    • Frequency: Quarterly
    • DOI: 10.18178/IJCEA
    • Editor-in-Chief: Prof. Dr. Shen-Ming Chen
    • Executive Editor: Jennifer X. Zeng
    • Abstracting/ Indexing: Chemical Abstracts Services (CAS), Ulrich's Periodicals Directory, CABI, Electronic Journals Library, Google Scholar, ProQuest,  Crossref, EBSCO, CNKI.
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Prof. Dr. Shen-Ming Chen
National Taipei University of Technology, Taiwan

IJCEA 2010 Vol.1(3): 225-229 ISSN: 2010-0221
DOI: 10.7763/IJCEA.2010.V1.38

Determination of Suitable Feedstock for Refineries Utilizing LP and NLP Models

H. Ganji, S. Zahedi, M. Ahmadi Marvast, S. Kananpanah, M. Sadi, S. Shokri

Abstract—One of the most vital steps in optimization and management of oil refineries is allocation of suitable feedstock. This becomes more crucial with fluctuation of crude oil price and down grading of its quality. The selected crudes should have suitable properties to meet the constraints of refinery units.The main crude properties which should be considered are boiling point curve, fractional specific gravity, fractional sulfur, bulk viscosity, RVP, Pour Point, metal content, bulk sulfur and bulk nitrogen content. In order to determine the optimum feedstock, a computer model was developed which contains different sections for crude oil characterization, optimum blending of petroleum cuts and modeling of refinery units. Several experiments were carried out on individual and blended crudes and the physical properties were measured and compared with the calculated results to validate the model. To determine the sulfur fraction in different cuts, the previously derived equations were tuned to cover wide range of crudes. The developed linear and nonlinear equations were utilized to determine the effects of variation of oil properties on distillation unit. Several test runs were collected from different refineries to validate the model.

Index Terms—Feedstock, LP, NLP, Refinery, Optimization


Cite: H. Ganji, S. Zahedi, M. Ahmadi Marvast, S. Kananpanah and M. Sadi, S. Shokri, "Determination of Suitable Feedstock  for  Refineries  Utilizing  LP  and  NLP  Models,"   International  Journal  of  Chemical Engineering and
vol. 1, no. 3, pp. 225-229, 2010. 

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