Special Session 7

Topics (Including but not limited to)

• Artificial Intelligence-driven Renewable Energy Generation and Hydrogen Production
  人工智能驱动可再生能源发电与制氢
• Fault Diagnosis and Intelligent Fault-Tolerant Technology for New Energy Equipment
  新能源设备故障诊断与智能容错技术
• Mechanism Analysis, Identification and Suppression of Wideband Oscillation in New Power System
  新型电力系统宽频振荡机理分析、识别与抑制
• Intelligent Inspection Path Planning and Inspection Signal Denoising Processing for Substations
  变电站智能巡检路径规划与信号降噪处理
• Advanced Sensing and Functional Materials for Smart Grids and Renewable Energy Systems
  智能电网与新能源系统的先进感知与功能材料

Chair: Assoc. Prof. Jingxuan Zhang, North China University of Science and Technology, China

Jingxuan Zhang is an associate professor in power electronics area with the College of Electrical Engineering, North China University of Science and Technology, Tangshan, China. He received his B.Sc. degree in electrical automation, M.Sc. degree in control science and engineering, and Ph.D. degree in control theory and control engineering all from Hebei University of Technology, Tianjin, China. His research interests include fault diagnosis, PHM and reliability assessment for power electronic in renewable energies, hydrogen energy and energy storage. He has authored more than 50 technical papers. He is a Director of Hydrogen Energy Storage Subcommittee in IEEE PES Energy Storage and Stationary Battery Satellite Committee-China. He is a Senior Member of China Electrotechnical Society. He is a frequent reviewer of more than 40 journals.

Co-chair: Assoc. Prof. Weichao Dong, Hebei University of Science and Technology, China

Weichao Dong is an associate professor in School of Electrical Engineering, Hebei University of Science and Technology, China. He received the Ph.D. degree in School of Artificial Intelligence, Hebei University of Technology. His research interests include artificial intelligence technology, hydrogen production from renewable energy sources and optimization and design of smart micro grid.

Co-chair: Dr. Jinping Liang, Lanzhou Jiaotong University, China

Jingping Liang is a lecturer in the new energy grid-connected control area with the School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu, China. She received her B.Sc. degree from Shanxi University in 2012, M.Sc. degree from Lanzhou Jiaotong University in 2015, and Ph.D. degree from Northwestern Polytechnical University in 2024. Her research interests include new energy grid-connected control technology, electrical equipment fault diagnosis technology, and multi-data source information fusion technology. She presides over and participates in multiple national and provincial-level research projects. She has published more than 10 academic papers and also serves as a reviewer for various international journals.

Co-chair: Assoc. Prof. Mingduo Li, North China University of Science and Technology, China

Mingduo Li is an associate professor in College of Electrical Engineering, North China University of Science and Technology, Tangshan, China. She received her B.Sc. and M.Sc. degree in electrical engineering from Hebei University of Technology, Tianjin, China and Northeastern University, USA. She received the Ph.D. degree in mining engineering and was dedicated to research on underground personnel positioning and signal processing. Her research interests include personnel positioning, signal processing, smart inspection of substations. She has published more than 20 papers and has led or participated in numerous research projects.

Co-chair: Dr. Peng Guo, Hebei University of Technology, China

Peng Guo received the M.Eng. degree from Hebei University of Science and Technology, Shijiazhuang, Hebei, China, in 2020, and the Ph.D. degree in electrical engineering from Hebei University of Technology, Tianjin, China, in 2025. He is currently a Postdoctoral Researcher at Hebei University of Technology. His research interests include high-precision sensing and fault diagnosis in smart grids, data-driven material modeling, and intelligent equipment design and analysis.