An Integrated Risk Management Model in Setting Up Resource and Energy Saving Processes Taking Complex Thermal Processing Systems as an Example
Abstract
Under the conditions of constantly growing complexity of the processes used in technological systems, the main risk management tasks cannot be solved by using the traditional methods implying exact representation of problem situations. This is because such tasks are characterized by a large number of parameters, uncertainty and data ambiguity. The external environmental conditions for such systems are characterized by instability and uncertainty, which are caused, on the one hand, by high variability of the external environment and, on the other hand, by uniqueness of the emerging problem situations.
The problem is formulated, and a cascade-composition integrated risk management model in setting up resource and energy saving processes is proposed taking complex thermal processing systems (CTPS) as an example. The proposed model is based on a fuzzy approach and on fuzzy model hybridization and integration methods.
The need for comprehensively managing the risks in setting up resource and energy saving processes in a CTPS is primarily stemming from the requirement of keeping the violation risks within the acceptable level. It should be noted that the acceptable level of risk can be established not only for violation of technological processes in a CTPS as a whole, but also for all stages and for individual technological processes.
The proposed cascade-composition model includes fuzzy models for carrying out a component-wise analysis of the technological processes in the CTPS, for estimating the resource and energy efficiency of technological processes, and for assessing the risks in setting up resource and energy savings.
The article describes an approach to solving the problem of integrated risk management in setting up resource and energy saving processes in the CTPS using the proposed model. The approach implies specification of different combinations of control parameters at each stage for all technological processes with taking into account all constraints imposed on these processes, and modeling and determining the combinations of control parameters that will make it possible to improve the resource and energy efficiency of technological processes in the CTPS while keeping the violation risks within the acceptable level.
The article presents the experimental results of integrated risk management in setting up resource and energy savings using the proposed model and approach taking as an example the process of drying phosphate pellets in the calcining conveyor machine. The obtained results are supposed to be used for integrated risk management in setting up resource and energy saving for various processes in CTPSs.
References
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Для цитирования: Борисов В.В., Дли М.И., Бобков В.И. Модель комплексного управления рисками при обеспечении ресурсо- и энергосбережения процессов на примере сложных теплотехнологических систем // Вестник МЭИ. 2019. № 5. С. 101—109. DOI: 10.24160/1993-6982-2019-4-101-109.
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Работа выполнена при поддержке: Министерства науки и высшего образования Российской Федерации (проект № 13.9597.2017/БЧ)
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1. GOST R 51897—2002. Menedzhment riska. Terminy i opredeleniya. (in Russian).
2. GOST R 51898—2002. Aspekty Bezopasnosti. Pravila Vklyucheniya v Standarty. (in Russian).
3. Butkarev A.A., Butkarev A.P., Zhomiruk P.A., Martynenko V.V., Grinenko N.V. Pellet Heating on Modernized OK-124 Roasting Machine. Steel in Translation. 2010;40;3:239—242.
4. Fan X.-H., Gan M., Jiang T., Yuan L.-S., Chen X.-L. Influence of .Flux Additives on iron Ore Oxidized Pellets. J. Central South University of Technology. 2010;17;4: 732—737.
5. Elgharbi S., Horchani-Naifer K., Férid M. Investigation of the Structural and Mineralogical Changes of Tunisian Phosphorite During Calcinations. J. Thermal Analysis and Calorimetry. 2015;119; 1:265—271.
6. Luis P., Van der Bruggen B. Exergy Analysis of Energy-intensive Production Processes: Advancing Towardsa Sustainable Chemical Industry. J. Chemical Techn. and Biotech. 2014; 89; 9:1288—1303.
7. Butkarev A.A., Butkarev A.P., Ptichnikov A.G., Tumanov V.P. Boosting the Hot-blast Temperature in Blast Furnaces by of Optimal Control System. Steel in Translation. 2015;45;3:199—206.
8. Bokovikov B.A., Bragin V.V., Shvydkii V.S. Role of the Thermal-inertia Zone in Conveyer Roasting Machines. Steel in Translation. 2014;44;8:595—601.
9. Petrosino A., Fanelli A.M., Pedrycz W. Fuzzy Logic and Applications. Springer, 2011.
10. Borisov V.V. Hybridization of Intellectual Technologies for Analytical Tasks of Decision-making Support. J. Computer Eng. and Informatics. 2014;2;1: 148—156.
11. Bobkov V.I., Borisov V.V., Dli M.I., Meshalkin V.P. Multicomponent Fuzzy Model for Evaluating the Energy Efficiency of Chemical and Power Engineering Processes of Drying of the Multilayer Mass of Phosphoresce Pellets. Theoretical Foundations of Chemical Eng. 2018;52;5:786—799.
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For citation: Borisov V.V., Dli M.I., Bobkov V.I. An Integrated Risk Management Model in Setting Up Resource and Energy Saving Processes Taking Complex Thermal Processing Systems as an Example. Bulletin of MPEI. 2019;5:101—109. (in Russian). DOI: 10.24160/1993-6982-2019-5-101-109.
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The work is executed at support: Ministry of Science and Higher Education of the Russian Federation (Project No. 13.9597.2017/БЧ)
