Digital Twin and AI-Enabled Engineering Applications for Modern Power Energy Systems

Submission Deadline: 31 December 2026 View: 627 Submit to Special Issue

Guest Editor(s)

Prof. Dr. Chuangxin Guo

Email: guochuangxin@zju.edu.cn

Affiliation: College of Electrical Engineering, Zhejiang University, Hangzhou, China

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Research Interests: digital twin, AI and control operation of modern power systems

Prof. Dr. Jian Qiu

Email: jianqiu@zju.edu.cn

Affiliation: College of Electrical Engineering, Zhejiang University, Hangzhou,  China

Homepage:

Research Interests: big data, Al and digital twin in smart grids

Prof. Dr. Xiaojing Wang

Email: wangxiaojing345@163.com

Affiliation: College of Electrical Engineering, Zhejiang University, Hangzhou, China

Homepage:

Research Interests: AI, digital twin, integrated energy & optimal operation of microgrids

Summary

The advancement of new-type power systems calls for intelligent technologies to address the integration of distributed energy resources, coordinated operation of generation-grid-load-storage, and secure and efficient energy utilization. Digital twin, artificial intelligence, and data-physical fusion have become key enabling tools with high engineering value for modeling, simulation, optimal dispatch, risk defense, and resilient operation of modern power grids.

This special issue focuses on Digital Twin and AI-Enabled Engineering Applications for Modern Power Energy Systems. It aims to collect high-quality original research on AI, digital twin, data-driven methods, and their practical implementations in energy forecasting, storage optimization, microgrid coordination, distribution network operation, and integrated energy management.

Suggested themes:
(1)Digital twin and data-physical fusion for power systems
(2)AI applications in energy forecasting and optimal operation
(3)Microgrid and integrated energy efficient utilization
(4)Resilient operation and risk defense of distribution networks with DG
(5)Intelligent planning, dispatch and maintenance for smart grids
(6)Intelligent Operation and Maintenance Optimization of Power Equipment

Keywords

Published Papers