Development of a kinetic model for catalytic reforming of naphtha and parameter estimation using industrial plant data

Mirko Z. Stijepovic, Aleksandra Vojvodic-Ostojic, Ivan Milenkovic, Patrick Linke

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

In the present paper, a semi-empirical kinetic model for catalytic reforming has been developed. In the developed model, the component "lumping" strategy is based on a paraffins, olefins, naphthalenes, and aromatics (PONA) analysis. "Activation energy lumps" are introduced to take into account different values of activation energies within specific reaction classes. The parameters of the model have been estimated by bench marking with industrial data. Simulation results have been found to be in very close agreement with plant data. One of the advantages of the present kinetic model is that it predicts the concentration of hydrogen and light gases very well. Because it is formulated from basic principles, this kinetic model with some modification can be applied to any catalytic reformer.

Original languageEnglish
Pages (from-to)979-983
Number of pages5
JournalEnergy and Fuels
Volume23
Issue number2
DOIs
Publication statusPublished - 19 Feb 2009

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Catalytic reforming
Naphthas
Parameter estimation
Industrial plants
Kinetics
Naphthalenes
Activation energy
Alkenes
Naphthalene
Paraffin
Paraffins
Olefins
Hydrogen
Gases
naphtha

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Fuel Technology
  • Energy Engineering and Power Technology

Cite this

Development of a kinetic model for catalytic reforming of naphtha and parameter estimation using industrial plant data. / Stijepovic, Mirko Z.; Vojvodic-Ostojic, Aleksandra; Milenkovic, Ivan; Linke, Patrick.

In: Energy and Fuels, Vol. 23, No. 2, 19.02.2009, p. 979-983.

Research output: Contribution to journalArticle

Stijepovic, Mirko Z. ; Vojvodic-Ostojic, Aleksandra ; Milenkovic, Ivan ; Linke, Patrick. / Development of a kinetic model for catalytic reforming of naphtha and parameter estimation using industrial plant data. In: Energy and Fuels. 2009 ; Vol. 23, No. 2. pp. 979-983.
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