Our energy system will be dominated by renewables, low-carbon technologies, and digital technology in order to deliver net zero. However, traditional mechanisms for modeling and control have been difficult to apply to this new system due to its fundamentally different characteristics, including limitations in terms of space and time scales. Additionally, data modeling often lacks the capability to perceive changes in asset operating status and key parameters, resulting in poor modeling accuracy.

The new energy system is more dispersed in space and time, and the complex interactions between various subjects and the autonomous behaviors of users bring significant challenges to modeling and control. The scale of system data has also increased significantly, presenting a new trend of time-space asynchrony and the fusion of information and energy. A Digital Twin can fully combine the advantages of mechanism modeling and data-driven modeling to build a high-fidelity hybrid model with clear physical meanings, strong extrapolation and generalization capabilities, and real-time interactions with real assets and systems. This will help realize the complete mapping and real-time dynamic interaction from the real world to the virtual space.

In order to promote research and applications of Digital Twins in the new energy system and wider energy efficiency, we propose this Research Topic. The topics welcomed in this collection are listed below (but not limited to):

1) Basic theories, specific implementation methods, and application technologies related to digital twin technology;

2) The application of digital twins in the operation of new power systems;

3) Application and methods of digital twin technology in power system analysis and control;

4) Multi-physical field modeling and simulation technology for digital twins;

5) Digital Twin-enabled energy system efficiency;

6) Case studies of using digital twin in energy efficiency;

7) Complex system perception and decision-making technology based on digital twins

8) Key technologies of swarm intelligence control based on multi-agent systems;

9) Other issues related to digital twins and swarm intelligence

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Frontiers in Energy Efficiency

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