The System of Models and Optimization of Operating Modes of a Catalytic Reforming Unit Using Initial Fuzzy Information

Batyr Orazbayev, Ainur Zhumadillayeva, Kulman Orazbayeva, Sandugash Iskakova, Balbupe Utenova, Farit Gazizov, Svetlana Ilyashenko and Olga Afanaseva
Additional contact information
Batyr Orazbayev: Faculty of Information Technologies, L.N. Gumilyov Eurasian National University, Nur-Sultan 010000, Kazakhstan
Ainur Zhumadillayeva: Faculty of Information Technologies, L.N. Gumilyov Eurasian National University, Nur-Sultan 010000, Kazakhstan
Kulman Orazbayeva: Department of Management, Kazakh University of Economics, Finance and International Trade, Nur-Sultan 020000, Kazakhstan
Sandugash Iskakova: Faculty of Information Technologies, Atyrau Oil and Gas University, Atyrau 060027, Kazakhstan
Balbupe Utenova: Faculty of Information Technologies, Atyrau Oil and Gas University, Atyrau 060027, Kazakhstan
Farit Gazizov: Department of Economics and Organization of Production, Kazan State Power Engineering University, 420066 Kazan, Russia
Svetlana Ilyashenko: Basic Department of Trade Policy, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Olga Afanaseva: Institute of Energy, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia

Energies, 2022, vol. 15, issue 4, 1-25

Abstract: The study aims to develop a system of models and a method for optimizing the operating modes of a catalytic reforming unit using fuzzy information, which makes it possible to effectively control the reforming process of the object under study. The object of study of this work is a catalytic reforming unit that has been operating for more than half a century and is characterized by the lack of clarity of some part of the initial information. The research methods are methods of system analysis, mathematical modeling, multicriteria optimization, and expert assessments, as well as methods of theories of fuzzy set theories, which allows formalizing and using fuzzy information, as well as experimental-statistical methods. As a result of the conducted research, the following main results were obtained. Based on a systematic approach, an effective methodology has been developed for developing a system of models of interconnected plant units using various types of available information, including fuzzy information. Using the proposed method, hybrid models have been developed to determine the volume of the produced catalyzate and its quality indicators. A scheme has been constructed for combining the developed models of the main units of the catalytic reforming unit into a single package of models. The built system of models makes it possible to systematically simulate the operation of the plant under study and improve the efficiency of the facility by increasing the volume of target products produced and improving its quality indicators. A statement of the problem of multicriteria optimization is obtained, taking into account the partial fuzziness of the initial information, and a heuristic method for its solution is developed, which is based on the use of knowledge, experience, and intuition of the decision-maker. The results of modeling and optimization show the effectiveness of the proposed fuzzy approach.

Keywords: installation of catalytic reforming; hydrogenated; catalysis; mathematical model; multicriteria optimization in a fuzzy environment; fuzzy information; methods of fuzzy set theories; heuristic method; decision-makers (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/4/1573/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/4/1573/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:4:p:1573-:d:754453

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().