Digital Twins for Energy-Related Applications

Submission Deadline:  1 July 2025

IEEE Access invites manuscript submissions in the area of Digital Twins for Energy-Related Applications.   

Emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), big data analytics, Blockchain Technology (BT) and cloud computing are accelerating the trend of Industry 4.0 digital transformation, creating enormous opportunities, and allowing for a paradigm shift in operation and control in energy sectors, such as thermal power plants, nuclear power plants, wind energy, solar energy and oil and gas installations. Building upon these technologies, digital twins (DTs), which are virtual representations of real-world physical objects, are gaining momentum as promising tools for the realization of intelligent energy production systems, and receiving significant interest from both the research and industrial communities. With DTs, the energy production sectors can achieve a real-time simulation environment that can be used for several purposes, including control, safety and reliability improvement, maintenance cost reduction, operational disruption minimization, operational efficiency improvement, profit maximization and precise intelligent decision-making possibilities.  In this context, DT is regarded as a promising enabling technology with the potential to revolutionize the energy system’s design, operation and optimization.

This Special Section covers all energy-related sectors, including thermal power plants, nuclear power plants, wind energy, solar energy and oil and gas installations. In the advent of industry 4.0, DT is a current trend for academic and industrial communities not only in the IEEE but also in many other institutions across the globe. The aim of this Special Section is to provide a platform for academic and industrial communities to share their new ideas and developments relevant to DTs, and to promote, collect and present recent research advancements including both methodological developments and practical deployments of DTs for energy-related applications.

The topics of interest include, but are not limited to:

  • DT design, data management, modeling and simulation
  • DT-enabling technologies for multi-physics modeling and analysis of energy production assets
  • DT architectural design, development and standard for emerging technologies in energy sectors
  • DT for lifetime prediction and reliability assessment
  • AI/ML-based DT approaches for Prognostics and System Health Management
  • Blockchains and Federated AI/ML-based DT design and development for energy systems
  • Grey-box based DT approaches for energy-related applications
  • Data fusion/assimilation techniques for DT development and management
  • DT-based risk-informed system health and asset management
  • Big-data-based intelligent prediction and assistant decision-making
  • DT-based energy equipment maintenance plan
  • DT-enabling technologies for safety and security assessment of energy production systems
  • Recent developments and future perspectives of DT in emerging technological applications in energy sector

 

We also highly recommend the submission of a video with each article as it significantly increases the visibility of articles.

Lead Editor: Enrico Zio, Politecnico di Milano, Italy and MINES Paris-PSL, CRC, France

Guest Editors:

    1. Syed Bahauddin Alam, University of Illinois Urbana-Champaign, USA
    2. Rui Kang, Beihang University, China

 

IEEE Access Editor-in-Chief: Prof. Mehrdad Saif, University of Windsor, Ontario, Canada

Article submission: Submit manuscripts to: http://ieee.atyponrex.com/journal/ieee-access

For information regarding IEEE Access, including its peer review policies and APC information, please visit the website http://ieeeaccess.ieee.org

For inquiries regarding this Special Section, please contact: enrico.zio@polimi.it.