IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i9p2180-d1140113.html
   My bibliography  Save this article

Mathematical Foundations for Modeling a Zero-Carbon Electric Power System in Terms of Sustainability

Author

Listed:
  • Anatoliy Alabugin

    (Department of Digital Economy and Information Technology, School of Economics and Management, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia)

  • Konstantin Osintsev

    (Department of Energy and Power Engineering, Institute of Engineering and Technology, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia)

  • Sergei Aliukov

    (Department of Automotive Engineering, Institute of Engineering and Technology, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia)

  • Zlata Almetova

    (Department of Automotive Engineering, Institute of Engineering and Technology, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia)

  • Yaroslav Bolkov

    (Department of Energy and Power Engineering, Institute of Engineering and Technology, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia)

Abstract

This article substantiates the relevance of mathematical methods and models for studying the management of the factorial parameters of regulating the decarbonization of regions of the Russian Federation. We present methods for the mathematical modeling of greenhouse gas emissions and for approximating functions for the study of processes in the thermal power industry and the economy. New models and methods are shown to increase the efficiency of designing electric power systems (EPSs). We establish that diverse companies must interact with institutions of education and science to achieve the main results of the study. This is achieved, firstly, by creating an EPS with a target of a zero-carbon footprint. Mathematical models of greenhouse gas emissions can be used to support this goal. We developed ways to account for carbon oxides and water streams. Stable interactions between systems in the innovation cycles of enterprises are ensured by methods combining a number of properties of the regulation of decarbonization. We describe methods to mathematically model greenhouse gas emissions and to approximate functions in the study of processes in the thermal power industry and economics. New research methods and techniques are proved to increase the efficiency of designing an EPS and can be used to reduce emissions. Digital twins should be modeled according to assessments on ensuring the stability of the balance area, with the goals of developing the EPS. Secondly, we substantiate methods for displaying singular processes of improving the balance of enterprise goals while coordinating the impact on the efficiency of standard and additional management functions. We additionally developed quality parameters for the use of additional functions in the foresight control of decarbonization goals. Thirdly, factorial parameters of additional control and regulation functions are implemented via a special system of technical accounting. This formed a big data database of new environmental quality and quality management indicators in the regulatory structure of industrial enterprises in the EPS. Additional functions of integration, combination, and acceleration of the impact of industrial enterprise quality indicators are organized on a digital platform to predict and plan indicators of integration and combination of these resources using neural networks.

Suggested Citation

  • Anatoliy Alabugin & Konstantin Osintsev & Sergei Aliukov & Zlata Almetova & Yaroslav Bolkov, 2023. "Mathematical Foundations for Modeling a Zero-Carbon Electric Power System in Terms of Sustainability," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2180-:d:1140113
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/9/2180/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/9/2180/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Klaus Mainzer, 2020. "Technology Foresight and Sustainable Innovation Development in the Complex Dynamical Systems View," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(4), pages 10-19.
    2. Kim, Yongjae, 2017. "The effect of process management on different types of innovations: An analytical modeling approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 771-779.
    3. Lafond, François, 2015. "Self-organization of knowledge economies," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 150-165.
    4. Ville Brummer & Totti Konnola & Ahti Salo, 2010. "Diversity in Foresight: A Practice of Selection of Innovation Ideas," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 4(4), pages 56-68.
    5. Gilbert Ahamer, 2018. "Applying Global Databases to Foresight for Energy and Land Use: The GCDB Method," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(4), pages 46-61.
    6. Hoegl, Martin & Schulze, Anja, 2005. "How to Support Knowledge Creation in New Product Development:: An Investigation of Knowledge Management Methods," European Management Journal, Elsevier, vol. 23(3), pages 263-273, June.
    7. Laurie J. Kirsch, 1996. "The Management of Complex Tasks in Organizations: Controlling the Systems Development Process," Organization Science, INFORMS, vol. 7(1), pages 1-21, February.
    8. Anatoliy Alabugin & Sergei Aliukov & Tatyana Khudyakova, 2022. "Review of Models for and Socioeconomic Approaches to the Formation of Foresight Control Mechanisms: A Genesis," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    9. Anatoliy Alabugin & Sergei Aliukov & Tatyana Khudyakova, 2022. "Models and Methods of Formation of the Foresight-Controlling Mechanism," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    Full references (including those not matched with items on IDEAS)

    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. Anatoliy Alabugin & Sergei Aliukov & Tatyana Khudyakova, 2022. "Review of Models for and Socioeconomic Approaches to the Formation of Foresight Control Mechanisms: A Genesis," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    2. Mähring, Magnus, 2002. "IT Project Governance: A Process-Oriented Study of Organizational Control and Executive Involvement," SSE/EFI Working Paper Series in Business Administration 2002:15, Stockholm School of Economics.
    3. Bart A. De Jong & Katinka M. Bijlsma-Frankema & Laura B. Cardinal, 2014. "Stronger Than the Sum of Its Parts? The Performance Implications of Peer Control Combinations in Teams," Organization Science, INFORMS, vol. 25(6), pages 1703-1721, December.
    4. Amit Mehra & Rajiv Dewan & Marshall Freimer, 2011. "Firms as Incubators of Open-Source Software," Information Systems Research, INFORMS, vol. 22(1), pages 22-38, March.
    5. Urszula Mikiewicz & Miroslaw Moroz, 2021. "Trade-Offs Occurring in the Process of Commercialization of SARS-CoV-2 Test in a Narrow Window of Opportunity," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 294-313.
    6. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.
    7. Il-Horn Hann & Jeffrey A. Roberts & Sandra A. Slaughter, 2013. "All Are Not Equal: An Examination of the Economic Returns to Different Forms of Participation in Open Source Software Communities," Information Systems Research, INFORMS, vol. 24(3), pages 520-538, September.
    8. Su Zhongfeng & Wang Donghan, 2018. "Entrepreneurial Orientation, Control Systems, and New Venture Performance: A Dominant Logic Perspective," Entrepreneurship Research Journal, De Gruyter, vol. 8(3), pages 1-17, July.
    9. Sandeep Rustagi & William R. King & Laurie J. Kirsch, 2008. "Predictors of Formal Control Usage in IT Outsourcing Partnerships," Information Systems Research, INFORMS, vol. 19(2), pages 126-143, June.
    10. Christian Jung-Gehling & Erik Strauss, 2018. "A Contemporary Concept of Organizational Control: Its Dependence on Shared Values and Impact on Motivation," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 70(4), pages 341-374, November.
    11. Rob Gleasure & Kieran Conboy & Lorraine Morgan, 2019. "Talking Up a Storm: How Backers Use Public Discourse to Exert Control in Crowdfunded Systems Development Projects," Information Systems Research, INFORMS, vol. 30(2), pages 447-465, June.
    12. Ling Xue & Gautam Ray & Bin Gu, 2011. "Environmental Uncertainty and IT Infrastructure Governance: A Curvilinear Relationship," Information Systems Research, INFORMS, vol. 22(2), pages 389-399, June.
    13. Suchandra Paul, 2018. "Crisis in Boeing 787 Dreamliner: An Investigation from Project Management Control Perspective," International Journal of Human Resource Studies, Macrothink Institute, vol. 8(4), pages 242251-2422, December.
    14. Johnson, William H.A., 2011. "Managing university technology development using organizational control theory," Research Policy, Elsevier, vol. 40(6), pages 842-852, July.
    15. Maren Gierlich-Joas & Thomas Hess & Rahild Neuburger, 2020. "More self-organization, more control—or even both? Inverse transparency as a digital leadership concept," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 921-947, November.
    16. Sebastian Goebel & Barbara E. Weißenberger, 2017. "The Relationship Between Informal Controls, Ethical Work Climates, and Organizational Performance," Journal of Business Ethics, Springer, vol. 141(3), pages 505-528, March.
    17. Rachel Levy & Damien Talbot, 2015. "Control by proximity: Evidence from the 'Aerospace Valley' Competitiveness Cluster," Regional Studies, Taylor & Francis Journals, vol. 49(6), pages 955-972, June.
    18. Simge Tuna & Stefano Brusoni & Anja Schulze, 2019. "Architectural knowledge generation: evidence from a field study," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(5), pages 977-1009.
    19. Ferasso, Marcos & Grenier, Corinne, 2021. "Fostering SME's co-development of innovative projects in biotech clusters: Extending the sets of enablers for the knowledge creation process," Technology in Society, Elsevier, vol. 67(C).
    20. Jack Shih-Chieh Hsu & Sheng-Pao Shih & Yu Wen Hung & Paul Benjamin Lowry, 2015. "The Role of Extra-Role Behaviors and Social Controls in Information Security Policy Effectiveness," Information Systems Research, INFORMS, vol. 26(2), pages 282-300, June.

    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:9:p:2180-:d:1140113. 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.