Special Issue on Digital Twins for Resilient and Optimal Operation of Cyber-Physical Energy Systems

Introduction:

As modern electrical power and energy systems evolve towards large-scale digitalisation, decentralisation and automation, the concept of 'digital twin' is emerging as a crucial enabler for planning and analysis, real-time monitoring and management, and the optimisation of cyber-physical energy systems.

By creating a dynamically updated virtual representation of the physical process (e.g., a power or energy system or its components) over a communication infrastructure, digital twins continuously receive real-time measurements and information to maintain digital models of varying complexity to support enhanced situational awareness and decision-making across the generation, transmission, distribution and consumption layers. Digital twins themselves can have different architectures, dependent on the expected functionality and the complexity of the observed/controlled physical process.

The increasing integration of power electronic-interfaced assets on the generation and demand sides escalates the complexity, uncertainty and operational coupling/interactions of future energy systems, leading to increased risks and operational costs. For instance, generation side assets include energy storage systems and variable energy sources such as wind farms and solar photovoltaics, while the demand side considers modern power-dense loads including electric vehicles, electrified buildings and large data centres. Realised through different architectures, digital twins are capable of supporting major power/energy system functionalities, e.g. monitoring, protection, control, real-time resilience assessment and optimal operation, while also enabling economic efficiency, market participation (both day-ahead and real-time), reduced CO₂ emissions and improved asset utilisation. Relying on fast and cyber-secure communication channels and reliable sensors, digital twins have a promising potential to even undertake real-time maintenance, preventive/corrective control and restoration. Through co-simulation, hardware-in-the-loop testing and data-driven approaches, digital twins may be used to validate new control and protection strategies.

This special issue aims to address the aforementioned challenges by bringing together leading researchers, engineers and practitioners from academia and industry to address the latest developments, research challenges and practical applications of digital twin technologies for cyber-physical energy systems.

Topics of interest for this call for papers include but are not restricted to:

• Digital twin architectures, frameworks and methodologies for cyber-physical energy systems
• Real-time monitoring, state estimation and situational awareness enabled by digital twins
• Digital twin applications for power system protection, fault diagnosis and disturbance analysis
• Digital twin-assisted power system control, stability enhancement and resilience improvement
• Digital twins for optimal operation, energy management and decision support in power systems
• Market-oriented and economic applications of digital twins for cyber-physical energy systems
• Digital twin-enabled integration and operation of wind energy, solar energy and energy storage systems
• Digital twin frameworks for electric vehicle integration, smart charging and vehicle-to-grid applications
• Data-driven, AI-enabled and hybrid-model digital twins for forecasting, anomaly detection and predictive maintenance
• Digital twins for transmission systems, distribution networks, microgrids, multi-energy systems and integrated system planning

Important Dates:

Submission Deadline: 30 June 2026

Final Manuscript Submission Deadline: 30 September 2026

Published (expected): November 2026

Guest Editor-in-Chief：

Vladimir Terzija, Newcastle University, UK. Email: vladimir.terzija@newcastle.ac.uk

Guest Editors:

• Hector Chavez, Universidad de Santiago de Chile, Chile. Email: hector.chavez@usach.cl 
• Sarasij Das, Indian Institute of Science, India. Email: sarasij@iisc.ac.in 
• Matthew Deakin, Newcastle University, UK. Email: matthew.deakin@newcastle.ac.uk 
• Carlos Ugalde Loo, Cardiff University, UK. Email: ugalde-looc@cardiff.ac.uk 
• Segundo Sevilla Felix Rafael, Zurich University of Applied Sciences, Switzerland. Email: segu@zhaw.ch 
• Amir Sajadi, University of Colorado Boulder, USA. Email: amir.sajadi@colorado.edu 
• Xiaozhe Wang, McGill University, Canada. Email: xiaozhe.wang2@mcgill.ca 
• Haoran Zhao, Shandong University, China. Email: hzhao@sdu.edu.cn 

Submission Instructions:

Please read the [Guide for Authors ] before submitting. All articles should be [submit online], please select [DT4CPES] on submission.