Including but not limited to the following contents:
Track 1: AI-driven optimization and decision-making of energy systems
Intelligent prediction and scenario generation for renewable energy power generation
Application of large language models in power grid dispatching
AI-assisted power system situational awareness and decision-making
Interpretable AI and trustworthy reinforcement learning for power grid control
Intelligent fault diagnosis and self-healing of power systems
Synergy optimization and scheduling of source, grid, load and storage
Intelligent edge control and cloud-edge collaboration in power grids
Multi-agent distributed optimization and game theory
Power system resilience assessment and intelligent enhancement
AI-driven analysis and trading strategies in power markets
Track 2: Large models and energy data intelligence
Large language models empowering power system operation and maintenance
Generative AI and energy scenario generation
Energy time series large models and load forecasting
Application of AI agents in energy management
Power system digital twin
Construction and reasoning of energy knowledge graphs
Federated learning and energy data privacy protection
Multimodal energy data fusion analysis
AI-assisted cybersecurity of power systems
Basic models and fine-tuning in the energy field
Track 3: Green low-carbon and intelligent energy systems
Data intelligent management of low-carbon power systems
Stable control of high penetration of new energy in power grids
Aggregation and regulation of virtual power plants
Orderly charging of electric vehicles and V2G strategies
Energy management of data centers and AI infrastructure
Intelligent optimization and control of energy storage systems
Optimization of hydrogen energy and multi-energy complementary systems
AI decision-making for carbon footprint accounting and carbon trading
Modeling and simulation of integrated energy systems
Collaboration between renewable energy and AI hardware energy efficiency