Modeling the economy of competing refineries and the industry as a whole causes a number of difficulties due to limited information about processing facilities. The development of Russian oil refining on the basis of large investments requires weighted assessments taking into account all available information. The modeling tools and the application of its results vary depending on the analysis of the individual refinery or their group. There is a need for tools to generate a set of evaluation parameters of Russian refineries that will provide comparable simulation results for each facility, regardless of the availability of information.
The purpose of the paper is to develop and test tools that allow to obtain the parameters of the refinery and form a Russian oil refining model based on them. In the absence of key data on the material balances of technological installations, flows of intermediates and their properties, prices for the sale of petroleum products and the purchase of oil, procedures were proposed to obtain estimates of the missing data. A number of assumptions were introduced to assess the material balances of technological processes of oil refineries. As a result, a set of estimates of the material balances of the refinery's technological processes has been obtained, which correspond to real ranges of values, satisfy the actual production of products and provide a condition for the economic optimality of the actual volume of crude oil processing. Having formed the price parameters and evaluated the material balances of the installations, a target economic function was compiled, the maximization of which is achieved by optimizing the volume of processed oil raw materials. Based on the model, a scenario forecast was built with detailing of indicators to the level of a separate refinery with the ability to analyze the dynamics of the corporate structure. The obtained results can be used as a basis for long-term management decisions regarding the development strategy of refineries or the preparation of marketing and investment policies of plants.
References
1. Ketabchi E., Mechleri E., Gu S., Arellano-Garcia H., Modelling andoptimisation approach of an integrated oil refinery and a petrochemical plant, Computer Aided Chemical Engineering, 2018, V. 44, pp. 1081-1086, http://doi:10.1016/B978-0-444-64241-7.50175-0
2. Sales L., Luna F., Prata B., An integrated optimization and simulation model for refinery planning including external loads and product evaluation, Braz. J. Chem., 2018, V. 35, no. 1, pp. 199-215, http://doi:10.1590/0104-6632.20180351s20160124
3. Oliveira F., Nunes P., Blajberg R., Hamacher S., A framework for crude oil scheduling in an integrated terminal-refinery system under supply uncertainty, European Journal of Operational Research, 2016, V. 252(2), pp. 635–645, http://doi:10.1016/j.ejor.2016.01.034
4. Ulanov V., Business development in emerging economies on the basis of limits and conditions of national strategies, Global Journal of Emerging Market Economies, 2019, V. 11, no. 1–2, pp. 37–47, http://doi:10.1177/0974910119871376
5. Klochko O., Grigorova A., Models of oil exporting countries’ inclusion into oil refining global value chains (In Russ.), Mirovaya ekonomika i mezhdunarodnye otnosheniya, 2020, no. 1, pp. 99–109, http://doi:10.20542/0131-2227-2020-64-1-99-109
6. Yakovlev A., Vyglovsky O., Demidova O., Bashlyk A., Incentives for repeated contracts in public sector: Empirical study of gasoline procurement in Russia, International Journal of Procurement Management, 2016, V. 9, no. 3, pp. 99–109, http://doi:10.1504/IJPM.2016.076305
7. Ulanov V., Performance indicators as a guide to making effective solutions in mineral commodities business (In Russ.), Mineral'nye resursy Rossii. Ekonomika i upravlenie, 2018, no. 2, pp. 30–33.
