IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i17p3800-d1232897.html
   My bibliography  Save this article

Modeling the Production Process of Fuel Gas, LPG, Propylene, and Polypropylene in a Petroleum Refinery Using Generalized Nets

Author

Listed:
  • Danail D. Stratiev

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria)

  • Angel Dimitriev

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria)

  • Dicho Stratiev

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria)

  • Krassimir Atanassov

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    Intelligent Systems Laboratory, Prof. Dr. Assen Zlatarov University, 1 “Prof. Yakimov” Blvd., 8010 Burgas, Bulgaria)

Abstract

The parallel processes involved in the production of refinery fuel gas, liquid petroleum gas (LPG), propylene, and polypropylene, occurring in thirteen refinery units, are modeled by the use of a Generalized Net (GN) apparatus. The modeling of the production of these products is important because they affect the energy balance of petroleum refinery and the associated emissions of greenhouse gases. For the first time, such a model is proposed and it is a continuation of the investigations of refinery process modelling by GNs. The model contains 17 transitions, 55 places, and 47 types of tokens, and considers the orders of fuel gas for the refinery power station, refinery process furnaces, LPG, liquid propylene, and 6 grades of polypropylene. This model is intended to be used as a more detailed lower-level GN model in a higher-level GN model that facilitates and optimizes the process of decision making in the petroleum refining industry.

Suggested Citation

  • Danail D. Stratiev & Angel Dimitriev & Dicho Stratiev & Krassimir Atanassov, 2023. "Modeling the Production Process of Fuel Gas, LPG, Propylene, and Polypropylene in a Petroleum Refinery Using Generalized Nets," Mathematics, MDPI, vol. 11(17), pages 1-17, September.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3800-:d:1232897
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/17/3800/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/17/3800/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    2. Pla, Benjamí n & Bares, Pau & Jiménez, Irina & Guardiola, Carlos & Zhang, Yahui & Shen, Tielong, 2020. "A fuzzy logic map-based knock control for spark ignition engines," Applied Energy, Elsevier, vol. 280(C).
    3. Danail Dichev Stratiev & Dicho Stratiev & Krassimir Atanassov, 2021. "Modelling the Process of Production of Diesel Fuels by the Use of Generalized Nets," Mathematics, MDPI, vol. 9(19), pages 1-10, September.
    4. Fahd Saeed Alakbari & Mysara Eissa Mohyaldinn & Mohammed Abdalla Ayoub & Ali Samer Muhsan & Ibnelwaleed A Hussein, 2021. "A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    5. Batyr Orazbayev & Dinara Kozhakhmetova & Ryszard Wójtowicz & Janusz Krawczyk, 2020. "Modeling of a Catalytic Cracking in the Gasoline Production Installation with a Fuzzy Environment," Energies, MDPI, vol. 13(18), pages 1-13, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Danail Stratiev & Angel Dimitriev & Dicho Stratiev & Krassimir Atanassov, 2023. "Generalized Net Model of Heavy Oil Products’ Manufacturing in Petroleum Refinery," Mathematics, MDPI, vol. 11(23), pages 1-19, November.
    2. Dicho Stratiev & Ivelina Shishkova & Nora Angelova & Danail D. Stratiev & Krassimir Atanassov, 2024. "Generalized Net Model of the Processes in a Petroleum Refinery—Part I: Theoretical Study," Mathematics, MDPI, vol. 12(19), pages 1-22, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Al-Falahi, Monaaf D.A. & Jayasinghe, Shantha D.G. & Enshaei, Hossein, 2019. "Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries," Energy, Elsevier, vol. 187(C).
    2. Hannan, M.A. & Ali, Jamal A. & Mohamed, Azah & Hussain, Aini, 2018. "Optimization techniques to enhance the performance of induction motor drives: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1611-1626.
    3. Kara Mostefa Khelil, Chérifa & Amrouche, Badia & Benyoucef, Abou soufiane & Kara, Kamel & Chouder, Aissa, 2020. "New Intelligent Fault Diagnosis (IFD) approach for grid-connected photovoltaic systems," Energy, Elsevier, vol. 211(C).
    4. Md Alamgir Hossain & Hemanshu Roy Pota & Walid Issa & Md Jahangir Hossain, 2017. "Overview of AC Microgrid Controls with Inverter-Interfaced Generations," Energies, MDPI, vol. 10(9), pages 1-27, August.
    5. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
    6. Kumar, Rajesh & Agarwala, Arun, 2016. "Renewable energy technology diffusion model for techno-economics feasibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1515-1524.
    7. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    8. Nie, S. & Huang, Charley Z. & Huang, G.H. & Li, Y.P. & Chen, J.P. & Fan, Y.R. & Cheng, G.H., 2016. "Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing," Applied Energy, Elsevier, vol. 162(C), pages 772-786.
    9. Zhang, Kai & Li, Jingzhi & He, Zhubin & Yan, Wanfeng, 2018. "Microgrid energy dispatching for industrial zones with renewable generations and electric vehicles via stochastic optimization and learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 356-369.
    10. Athanasios Kolios & Varvara Mytilinou & Estivaliz Lozano-Minguez & Konstantinos Salonitis, 2016. "A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs," Energies, MDPI, vol. 9(7), pages 1-21, July.
    11. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.
    12. Mustapha Habib & Elmar Bollin & Qian Wang, 2023. "Battery Energy Management System Using Edge-Driven Fuzzy Logic," Energies, MDPI, vol. 16(8), pages 1-18, April.
    13. Rivero-Iglesias, Jose M. & Puente, Javier & Fernandez, Isabel & León, Omar, 2023. "Integrated model for the assessment of power generation alternatives through analytic hierarchy process and a fuzzy inference system. Case study of Spain," Renewable Energy, Elsevier, vol. 211(C), pages 563-581.
    14. Kumar, N.J. Vinoth & Thameem Ansari, M. Mohamed, 2015. "A new design of dual-mode Type-II fuzzy logic load frequency controller for interconnected power systems with parallel AC–DC tie-lines and superconducting magnetic energy storage unit," Energy, Elsevier, vol. 89(C), pages 118-137.
    15. Muhammed Cavus & Dilum Dissanayake & Margaret Bell, 2025. "Deep-Fuzzy Logic Control for Optimal Energy Management: A Predictive and Adaptive Framework for Grid-Connected Microgrids," Energies, MDPI, vol. 18(4), pages 1-25, February.
    16. Rodríguez-López, Miguel A. & López-González, Luis M. & López-Ochoa, Luis M. & Las-Heras-Casas, Jesús, 2016. "Development of indicators for the detection of equipment malfunctions and degradation estimation based on digital signals (alarms and events) from operation SCADA," Renewable Energy, Elsevier, vol. 99(C), pages 224-236.
    17. Huang, Zhen & Li, Zeng-Yao & Tao, Wen-Quan, 2017. "Numerical study on combined natural and forced convection in the fully-developed turbulent region for a horizontal circular tube heated by non-uniform heat flux," Applied Energy, Elsevier, vol. 185(P2), pages 2194-2208.
    18. Medjber, Ahmed & Guessoum, Abderrezak & Belmili, Hocine & Mellit, Adel, 2016. "New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system," Energy, Elsevier, vol. 106(C), pages 137-146.
    19. Wajahat Ullah Khan Tareen & Muhammad Aamir & Saad Mekhilef & Mutsuo Nakaoka & Mehdi Seyedmahmoudian & Ben Horan & Mudasir Ahmed Memon & Nauman Anwar Baig, 2018. "Mitigation of Power Quality Issues Due to High Penetration of Renewable Energy Sources in Electric Grid Systems Using Three-Phase APF/STATCOM Technologies: A Review," Energies, MDPI, vol. 11(6), pages 1-41, June.
    20. Nkounga, Willy Magloire & Ndiaye, Mouhamadou Falilou & Cisse, Oumar & Grandvaux, Françoise & Tabourot, Laurent & Ndiaye, Mamadou Lamine, 2022. "Automatic control and dispatching of charging currents to a charging station for power-assisted bikes," Energy, Elsevier, vol. 246(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3800-:d:1232897. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.