Special Session 2

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Session Chair

Qiushi Cui
Associate Professor
Chongqing University, China
Special Research Fellow
Huairou Laboratory, China

 

Special Session 2: AI‑Enabled Smart Grids and Renewable Energy Integration

专题二:人工智能赋能的智能电网与可再生能源并网


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Session Description

The large-scale integration of wind, photovoltaic and other distributed renewable energy brings prominent uncertainties, stochastic fluctuations and complex coupling challenges to modern smart grids. Artificial intelligence, machine learning and data-driven technologies have become powerful enablers to tackle critical bottlenecks in renewable accommodation, grid perception, protection-control decision-making and real-time simulation of cyber-physical power systems.

This special session aims to gather academic researchers and industry practitioners to report original theoretical research, algorithm innovations, real-world case studies and digital-twin applications at the intersection of artificial intelligence, smart grid operation and renewable energy integration. We welcome high-quality submissions covering AI-augmented forecasting, intelligent protection & control, real-time simulation, resilience enhancement and practical deployment for high-renewable power systems. This session will foster cross-disciplinary exchanges and inspire new solutions for building secure, flexible and sustainable future energy infrastructures.


Topics of Interest (including but not limited to)
  • AI-based wind/solar and flexible load forecasting
  • AI-enhanced protection and control for high-renewable grids
  • Machine learning for grid situational awareness and fault diagnosis
  • AI-assisted real-time simulation and power system digital twin
  • AI-driven optimal scheduling of distributed energy resources
  • Data-physics hybrid modeling for smart grids
  • Reinforcement learning and large-model applications in grid resilience
  • Edge-AI for distributed renewable integration
  • Test-bed verification and practical cases of AI-enabled power grids
  • Trustworthy and interpretable AI for energy systems

Important Dates
October 05, 2026 Submission Deadline
October 30, 2026 Notification of Abstract and Full Paper Acceptance / Rejection
November 15, 2026 Registration Ends