Session 27: Physics and Data Informed Intelligence for Power, Energy, and Electricity Markets

“面向电力、能源及电力市场的物理与数据融合智能方法”

Session 27

Physics and Data Informed Intelligence for Power, Energy, and Electricity Markets
“面向电力、能源及电力市场的物理与数据融合智能方法”

As power and energy systems transition toward high penetrations of renewable energy resources, distributed assets, and flexible demand-side technologies, system operation is increasingly shaped by the interplay of physical dynamics, market mechanisms, behavioral responses, and data-driven decision processes. Electricity and flexibility markets have become integral to system operation, influencing resource allocation, price formation, and real-time control. In such coupled physical–market environments, traditional modeling and operational approaches—often relying on simplified physical assumptions or purely data-driven methods—face growing challenges in capturing complex interactions, uncertainty propagation, and dynamic system responses.
Recent advances in sensing, communication, and data acquisition have significantly enhanced system and market observability, enabling the integration of physics-based models with data-informed intelligence. Physics-informed learning, hybrid modeling, and data-supported market analysis offer new opportunities to improve system understanding, decision robustness, and coordination between physical feasibility and economic efficiency. Nevertheless, challenges remain in ensuring interpretability, maintaining physical and market consistency, and supporting reliable operation and market participation under uncertainty, extreme events, and rapidly changing conditions.
This session focuses on physics- and data-informed intelligent methods for the modeling, analysis, and operation of power and energy systems and their associated markets, providing a forum for exchanging advances at the intersection of systems, markets, and intelligent decision-making.

Topics (Including but not limited to)

Physics- and data-informed modeling of power and energy systems 电力与能源系统的物理与数据融合建模方法
Hybrid physical–data-driven methods for system analysis and control 面向系统分析与控制的物理–数据驱动混合方法
Modeling and operation of flexibility resources and aggregated demand 灵活性资源与聚合需求的建模与运行
Electricity and flexibility market modeling and analysis 电力市场与灵活性市场的建模与分析
Coupled physical–market dynamics and system–market interactions 物理系统–市场机制耦合动力学及系统–市场交互机理
Data-supported market clearing, pricing, and decision-making 数据支撑的市场出清、定价与决策方法
Uncertainty-aware and stochastic modeling in power systems and markets 面向不确定性的电力系统与市场随机建模方法
Learning-based state estimation and system monitoring 基于学习的状态估计与系统监测
Physics-informed machine learning for energy systems 面向能源系统的物理信息引导机器学习方法
Market-oriented operation and control of distributed energy resources 分布式能源资源的市场导向运行与控制
Robust and adaptive decision-making under extreme events and uncertainty 极端事件与不确定性条件下的鲁棒与自适应决策方法
Cyber-physical and cyber-economic aspects of power and energy systems 电力与能源系统中的信息物理与信息经济问题

Chair: Dr. Yunfeng Ma, Yancheng Teachers University, China

Yunfeng Ma received his Ph.D. degree in Electrical Engineering from North China Electric Power University and was a joint doctoral researcher at the University of Manchester, UK. He is currently a Lecturer at Yancheng Normal University and serves as a research coordinator in the School of Physics and Electronic Engineering. His research focuses on high-penetration renewable energy microgrids, virtual power plants, demand response, and ancillary services under market-oriented power system operation. Dr. Ma has published extensively in top-tier international journals and has participated in the development of two IEEE international standards in the field of power and energy systems. He has led and contributed to multiple national and provincial research projects and holds several invention patents related to flexible load aggregation and control. His work emphasizes the integration of power system operation theory with practical engineering applications and emerging market mechanisms.

Co-chair: Dr. Chao Zhang, Yancheng Institute of Technology, China

Chao Zhang received his Ph.D. degree in Electrical and Electronic Engineering from the University of Manchester, UK. He is currently a Lecturer at Yancheng Institute of Technology and a postdoctoral researcher at Southeast University. His research interests include modeling and state monitoring of renewable energy systems, time-series prediction for energy systems, and flexible service provision and control in distribution networks. He has published more than ten papers as first or corresponding author in leading journals such as IEEE Transactions series and Applied Energy. Dr. Zhang has participated in the development of two IEEE international standards related to power and energy systems. Prior to his academic career, he worked on algorithm research and development at major technology companies including Baidu and Hikvision, gaining extensive industrial experience in data-driven algorithms and large-scale information systems. His research has been supported by projects funded by the China Postdoctoral Science Foundation, UK EPSRC, and major power grid enterprises.

Co-chair: Dr. Hui Xiao, Wuhan University, China

Dr. Hui Xiao is is currently a lecturer at the School of Electrical and Automation Engineering, Wuhan University. He is a member of the Research Team for New Power Distribution System Technology and Safety (led by Professors Xuzhu Dong and Bo Wang). His research focuses on digital twin technology for distribution networks, new-type power distribution systems, and the industrial Internet. He has presided over two sub-projects of the National Science and Technology Major Project on Smart Grid 2030, one Postdoctoral Science Foundation project, four scientific research projects funded by the headquarters of State Grid and China Southern Power Grid, as well as several industry-funded projects. As the first or corresponding author, he has published more than twenty papers in prestigious international journals. In terms of academic service, Dr. Xiao serves as a Youth Editorial Board Member for Protection and Control of Modern Power Systems, Renewable and Sustainable Energy, Digital Twins and Applications, Chain, et al. He is also a Technical Forum Speaker at the 40th Annual Academic Conference on Electrical Power Systems and Automation (CUS-EPSA), Poster Section Chair for the 2025 IEEE International Conference on Intelligent Power and Energy Systems (IEEE IPET 2025), and Session Speaker at the 4th International Conference on Intelligent Power and Systems (ICIPS 2024). Additionally, he serves as a young expert in the CIGRE WG D2.67 working group and a member of the expert group for the China Association for Science and Technology's New Generation Artificial Intelligence Technology Roadmap in the New Energy Field.

Call for Papers Timeline / 征稿时间

Submission of Full Paper： March 15th, 2026
投稿截止日： 2026年3月15日
Notification Deadline： March 25th, 2026
通知书发送： 2026年3月25日
Registration Deadline： April 1st, 2026
注册截止日期： 2026年4月1日

Submission Guideline / 投稿指南

Template Download: Formatting.doc (文章模板)

Submit Now: Electronic Submission System (投稿链接)