IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-030-94617-3_4.html
   My bibliography  Save this book chapter

Digital Revolution in the Energy Sector: Effects of Using Digital Twin Technology

In: Digital Transformation in Industry

Author

Listed:
  • Wadim Strielkowski

    (University of California Berkeley)

  • Gordon Rausser

    (University of California Berkeley)

  • Evgeny Kuzmin

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences)

Abstract

The energy sector today is undergoing the digital revolution. The Internet of Things (IoT) and its subset, the Internet of Energy (IoE), that comprise, for example, smart meters, artificial intelligence (AI), or virtual reality (VR) with their practical application to the energy sector all together contribute to the enhancement of the smart energy grids of the future. Our paper focuses on the overview of the digital twins’ technology that are increasingly used in the smart grids. We discuss their application and usefulness for the improvement of the safety, security and reliability of the energy networks that include a two-way flow of information and power. Furthermore, we examine various types of digital twins and show use cases related to design, operation, control and safety of systems, testing, regulation, operator training and maintenance planning for energy utilities. Our research provides some innovative examples that might become the inspiration for the policy-makers and stakeholders working in the field of energy economics and policy.

Suggested Citation

  • Wadim Strielkowski & Gordon Rausser & Evgeny Kuzmin, 2022. "Digital Revolution in the Energy Sector: Effects of Using Digital Twin Technology," Lecture Notes in Information Systems and Organization, in: Vikas Kumar & Jiewu Leng & Victoria Akberdina & Evgeny Kuzmin (ed.), Digital Transformation in Industry, pages 43-55, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-94617-3_4
    DOI: 10.1007/978-3-030-94617-3_4
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Victoria Akberdina & Wadim Strielkowski & Natalia Linder & Sergey Kashirin & Lyudmila Shmeleva, 2023. "Information Technology and Digital Sufficiency for Building the Sustainable Circular Economy," Energies, MDPI, vol. 16(3), pages 1-14, January.
    2. Xing Liu & Xiaojing Zhang & Aliasghar Baziar, 2023. "Hybrid Machine Learning and Modified Teaching Learning-Based English Optimization Algorithm for Smart City Communication," Sustainability, MDPI, vol. 15(15), pages 1-20, July.

    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:spr:lnichp:978-3-030-94617-3_4. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.