Cyber physical energy systems are pervasive in modern society, from electric power grid to microgrid, from home energy systems to data centers. Artificial intelligence is fundamentally reshaping the research and practice in this field, including but not limited to stability analysis, economic scheduling, and online dispatching. The scope of this special issue includes, but is not limited to, the following topics:

• AI-based methods for dynamic stability assessment in power systems.
• Machine learning techniques for predicting and mitigating power system instabilities.
• Data-driven approaches for stability monitoring and control in power systems.
• AI-driven optimization models for economic dispatch.
• Intelligent algorithms for demand-side management and load forecasting.
• Reinforcement learning for real-time energy pricing and scheduling.
• AI-enabled real-time dispatching strategies for energy systems.
• Machine learning for adaptive control and dispatch in smart grids.
• Predictive analytics for enhancing the efficiency of dispatch operations.

All manuscripts submitted to the special issue will be subjected to peer review. Prospective authors should submit an electronic copy of their completed manuscript to https://mc03.manuscriptcentral.com/cai with “Special Issue on AI for Cyber Physical Energy Systems” marked in the cover letter.

Important Date

Manuscript Due: December 31, 2025

Guest Editors

Prof. Qing-Shan Jia

Director, Institute of Systems Engineering, Department of Automation, Tsinghua University, China

E-mail: jiaqs@tsinghua.edu.cn

Dr. Jiazhou Wang

Center for Intelligent and Networked Systems, Department of Automation, Tsinghua University, China

E-mail: wangjiazhou@tsinghua.edu.cn