Chair: Jiaqi Ruan, Sichuan University, China

Vice Chair 1: Bo Li, Tsinghua University, China

Vice Chair 2: Yibo Ding, The Hong Kong Polytechnic University, Hong Kong, China

As global power systems accelerate their transition toward a low-carbon and highly decentralized future, the large-scale integration of intermittent renewable generation, distributed energy resources, and flexible loads has introduced unprecedented operational uncertainties and complexities. To ensure grid reliability, economic efficiency, and sustainability under these evolving conditions, there is a pressing need to transcend traditional deterministic approaches and embrace advanced artificial intelligence (AI)-driven paradigms. AI-driven intelligence—spanning deep learning, reinforcement learning, knowledge representation, and large-scale neural architectures—serves as a transformative enabler for the perception, cognition, and autonomous decision-making required in next-generation power grids. This special session focuses on the theoretical foundations and practical implementations of AI-driven methodologies for forecasting, monitoring, optimization, and scheduling, aiming to provide a premier international forum for researchers, engineers, and practitioners to share state-of-the-art innovations and real-world applications that address the critical challenges of intelligent modern power systems.

1. AI-enhanced forecasting techniques for renewable generation and multi-energy loads, including but not limited to probabilistic forecasting, scenario generation, and spatiotemporal deep learning methods
2. AI-driven power system state estimation and topology identification
3. AI-driven optimization and intelligent control of flexible resources (e.g., energy storage systems, virtual power plants, data centers, and electric vehicles)
4. Risk-aware operational strategies in low-carbon grids, encompassing AI-assisted risk assessment, risk transfer mechanisms, and resilient scheduling under uncertainty
5. Interpretable and trustworthy AI methods for power system operation, decision support, and human-machine collaborative control
6. Emerging applications of foundation models and large language models in grid forecasting, real-time monitoring, and autonomous dispatching

Chair: Bo Liu, Tianjin University, China

Vice Chair 1: Peng Lu, China Agricultural University, China

Vice Chair 2: Chunyi Huang, Shanghai Jiao Tong University, China

Vice Chair 3: Fangyuan Si, Beijing Jiaotong University, China

Vice Chair 4: Kangping Li, Shanghai Jiao Tong University, China

State monitoring and sensing across generation, grid, load, and storage serve as a critical foundation for the scientific planning and operational optimization of power system. With the widespread deployment and application of various sensing devices in power system, data-driven approaches for smart grid planning and operation are receiving increasing attention. In the face of multiple challenges associated with new-type power system, successful applications of artificial intelligence across various fields have injected new momentum, creating fresh development opportunities for smart sensing and data analytic technologies in modern power system. This workshop aims to bring together diverse perspectives to explore the latest advances and future directions in this field.

1. Smart Grid
2. New-type Power System
3. Smart Sensing
4. AI for Electric Power System
5. Advanced Data Analytics

The rapid growth of artificial intelligence and large-scale computing infrastructure is reshaping the interaction between data centers and power systems. AI data centers are evolving from conventional electricity consumers into highly dynamic and potentially flexible grid participants, characterized by strong coupling among computing, communication, electrical, thermal, and storage processes. This transformation introduces new challenges to power system planning, operation, security, and resilience. This special session aims to bring together researchers and practitioners from power systems, data centers, optimization, control, and artificial intelligence to discuss emerging theories, methods, and technologies for coordinated power-computing systems. The session seeks to promote interdisciplinary collaboration and advance the secure, flexible, low-carbon, and resilient integration of future computing infrastructure with power systems.

1. Computing-load modeling and cross-domain coupling
2. Coordinated infrastructure planning and grid integration
3. Clean-energy supply and carbon-aware operation
4. Computing flexibility and grid-interactive operation
5. Multi-timescale coordination under uncertainty
6. Multi-layer storage and grid-supportive control
7. Dynamic security, stability, and wide-frequency-range oscillations
8. Resilience and restoration of coupled infrastructures
9. Demand response, ancillary services, and market design
10. AI methods, digital twins, and experimental validation

Chair: Wei Lin,  Chongqing University, China

Vice Chair 1: Shibo Chen, South China University of Technology, China

Vice Chair 2: Xiang Pan, Lingnan University, Hong Kong, China

With the large-scale integration of diverse resources, including renewable energy, energy storage, and flexible loads, power system operation is evolving from the traditional centralized and relatively deterministic paradigm toward multi-agent coordination, high uncertainty, and multi-timescale interactions. Power system operating conditions are becoming increasingly complex, while the types of resources involved in dispatch and control are becoming more diverse, placing higher demands on both decision-making efficiency and quality. Conventional operational decision-making approaches that rely on accurate physical models, rule-based experience, and online optimization are facing new challenges in terms of adaptability to complex operating conditions, rapid response capability, and multi-objective coordination. In recent years, artificial intelligence (AI) has demonstrated significant potential in complex feature extraction, nonlinear relationship modeling, fast inference, and autonomous decision-making, providing new technological pathways for enhancing the intelligence of power system operation and decision-making. This special session focuses on theoretical methods and key technologies of AI for the operation and decision-making of new-type power systems, and aims to provide a platform for presenting and exchanging the latest research advances in AI-enabled safe and efficient power system operation and decision-making.

1. AI-driven power system state perception and operational assessment technologies
2. AI-driven power system optimal dispatch and coordinated control technologies
3. Intelligent risk analysis and decision support technologies for secure power system operation
4. Intelligent decision-making and autonomous control technologies for complex operating conditions
5. Power system operational decision-making methods integrating physical knowledge and artificial intelligence