Methods for Developing Models in a Fuzzy Environment of Reactor and Hydrotreating Furnace of a Catalytic Reforming Unit

Batyr Orazbayev,Kulman Orazbayeva,Kanagat Dyussekeyev,Ainur Zhumadillayeva,Lyailya Kurmangaziyeva,Sandugash Iskakova

doi:10.3390/app11188317

Abstract

Methods for the development of fuzzy and linguistic models of technological objects, which are characterized by the fuzzy output parameters and linguistic values of the input and output parameters of the object are proposed. The hydrotreating unit of the catalytic reforming unit was investigated and described. On the basis of experimental and statistical data and fuzzy information from experts and using the proposed methods, mathematical models of a hydrotreating reactor and a hydrotreating furnace were developed. To determine the volume of production from the outlet of the reactor and furnace, nonlinear regression models were built, and fuzzy models were developed in the form of fuzzy regression equations to determine the quality indicators of the hydrotreating unit—the hydrogenated product. To identify the structure of the models, the ideas of sequential inclusion regressors are used, and for parametric identification, a modified method of least squares is used, adapted to work in a fuzzy environment. To determine the optimal temperature of the hydrotreating process on the basis of expert information and logical rules of conditional conclusions, rule bases are built. The constructed rule bases for determining the optimal temperature of the hydrotreating process depending on the thermal stability of the feedstock and the pressure in the hydrotreating furnace are implemented using the Fuzzy Logic Toolbox application of the MatLab package. Comparison results of data obtained with the known models, developed models and real, experimental data from the hydrotreating unit of the reforming unit are presented and the effectiveness of the proposed approach to modeling is shown.

Highlights

At present, the market of oil products of the Republic of Kazakhstan, as in other states, dictates the intensive development of the processes of deep oil refining and the production of high-quality and environmentally friendly motor fuels [1,2]
Sci. 2021, 11, x FOR PEER REVIpEaWrametric2 identification, a mathematical model that allows us to determine the volume of hydrogenate from the outlet of the reactor R-1, depending on xi, i = 1, 5, is obtained in the form:
To determine the volume of hydrogenate, i.e., of the target product from the outlet of the hydrotreating reactor R-1 using the methods of sequential inclusion of regressors and least squares on the basis of the experimental statistical data package and the REGRESS software package, a statistical model was built that makes it possible to determine the volume of hydrogenate from the outlet of the reactor depending on the input, operating parameters xi, i = 1, 5

Summary

Introduction

The market of oil products of the Republic of Kazakhstan, as in other states, dictates the intensive development of the processes of deep oil refining and the production of high-quality and environmentally friendly motor fuels [1,2] In this regard, there are problems of optimizing the operating modes of technological objects of deep oil refining according to economic and environmental criteria in the presence of various restrictions arising in production. The process of formalizing and solving problems of developing mathematical models, optimization problems in the presence of conflicting criteria, i.e., decision-making and management tasks for many technological objects of oil refining production, are complicated by the multi-criteria and fuzzy initial information [4,5,6]. The development of mathematical support for intellectualized decision support systems for the optimal management of oil refining facilities in a fuzzy environment based on the knowledge and experience of experts are currently very important and urgent tasks of science and oil refining

Objectives

Methods

Results

Discussion

Conclusion