Hydrotreating unit models based on statistical and fuzzy information

Alua Tanirbergenova, Batyr Orazbayev, Yerbol Ospanov, Sholpan Omarova, Ildar Kurmashev

Abstract


This paper presents the results of mathematical models’ development for hydrotreating reactor, stripping соlumn, absorbers and hydrotreating furnace which are basic units of hydrotreating block in catalytic reforming unit. Since these objects of modeling in reforming unit of Atyrau refinery operate in conditions of insufficiency and fuzziness of the initial information, their mathematical models are developed on the basis of a systematic approach, using available information of different nature (experimental-statistical data, fuzzy information from the experts), with appropriate methods of construction for mathematical models. Mathematical models, describing the dependence of the production output from the hydrotreating reactor, columns and furnace, are designed as a nonlinear regression models based on experimental-statistical data. Whereas models, evaluating the quality indicators of generated products from the hydrotreating reactor and columns, i.e., hydrogenation, hydrogen-containing and hydrocarbon-containing gases are built based on fuzzy information from specialists-experts in the form of fuzzy multiple regression equations. We have plotted the graph for the dependence of hydrogenation products output on the temperature in the hydrotreating reactor. To describe the dependence of the optimum temperature value in hydrotreating process on raw material quality, a linguistic model is designed based on compositional rules of inference and fuzzy information. Membership functions of fuzzy parameters are constructed for linguistic models.

Keywords


Hydrotreating, Hydrotreater, Hydrogenation, Hydrotreating reactor, Mathematical model, Fuzzy information, Membership function, Fuzzy model

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DOI: http://dx.doi.org/10.21533/pen.v9i4.2307

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Copyright (c) 2021 Alua Tanirbergenova, Batyr Orazbayev, Yerbol Ospanov, Sholpan Omarova, Ildar Kurmashev

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License