Session 3: Intelligent Wind Farm

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👤 Session Chair(s) and Speakers

Yan Jie

Dr. Yan Jie is a full Professor and Ph.D. Supervisor at North China Electric Power University's School of New Energy and a researcher at the State Key Laboratory of New Energy Power Systems. She was honored with the CAST Young Elite Scientist Program (2020), Beijing New Star Program (2023), Outstanding Young Talent Award from the China Renewable Energy Society (2023), and Youth Science and Technology Award from the China Electrotechnical Society (2024). She serves as a package lead of IEA Wind Task 36, an IEC TC8/SC8A expert, and associate editor for four SCI journals including IEEE Trans. on Sustainable Energy. Her research focuses on wind power forecasting and operational control. She leads one national key R&D project, two NSFC projects, and over ten industry projects. She has published 50 SCI papers as first/corresponding author, authored one textbook, co-edited one book, and holds 14 invention patents, including a Gold Award at the Geneva International Exhibition of Inventions.

📋 Session Abstract

Against the backdrop of accelerating global energy transition, wind energy development is moving from a phase of "scale expansion" to "intelligent operation." However, challenges such as wind resource uncertainty, complex terrain adaptability, high operation and maintenance costs, and volatile electricity markets severely constrain the economic viability and reliability of wind power. This session focuses on how artificial intelligence, big data, digital twins, and advanced control theory can be leveraged to close the full-chain intelligent loop of wind farms—from resource assessment, design, operation, maintenance, to multi-energy coordination.

We welcome contributions on the following frontier topics, including but not limited to:

  • High-resolution resource mapping based on multi-source remote sensing and machine learning;
  • Intelligent micro-siting and collection system optimization for cost reduction and efficiency improvement;
  • Wind farm flow field modeling and simulation using CFD, reduced-order models, and data-driven methods;
  • Coordinated control strategies considering fatigue loads and wake effects;
  • Ultra-short-term and short-term power forecasting;
  • Intelligent bidding and risk-hedging algorithms for electricity markets;
  • Early fault diagnosis and health condition assessment based on wind turbine operational signatures;
  • Coordinated optimal dispatch of wind-solar-storage-hydrogen multi-energy complementary systems.