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Session 14: AI assisted Renewable Energy System Scheduling, Operation and Maintenance

“基于人工智能辅助的可再生能源系统规划、运行与维护”

Session 14

AI assisted Renewable Energy System Scheduling, Operation and Maintenance
“基于人工智能辅助的可再生能源系统规划、运行与维护”

Renewable energy sources such as solar, wind, and hydropower are increasingly becoming the backbone of the global energy infrastructure. However, the scheduling, operation and maintenance of renewable energy systems pose unique challenges due to their intermittent nature, complex equipment, and often remote locations. The AI - assisted solution can offer transformative solutions to enhance efficiency, reliability, and cost-effectiveness. This session welcomes contributions that noval AI assisted applications in renewable system scheduling, power forecasting, performance optimization, conditional monitoring, grid Integration and management, and so on. By leveraging AI techniques, this research seeks to contribute to the sustainable development of renewable energy systems, and accelerating the global transition to a clean energy future.

Chair: Assoc. Prof. Huan Long, Southeast University, China

Huan Long received the B.Eng. degree from Huazhong University of Science and Technology, Wuhan, China, in 2013, and the Ph.D. degree from the City University of Hong Kong, Hong Kong, in 2017. She is currently an Associate Professor with the School of Electrical Engineering, Southeast University, Nanjing, China. Her research fields include artificial intelligence applied in modeling, optimizing, monitoring the renewable energy system and power system.

Co-chair: Prof. Zijun Zhang, City University of Hong Kong, Hong Kong, China

Prof. Zijun Zhang received his B.Eng. degree in Systems Engineering and Engineering Management from the Chinese University of Hong Kong, Hong Kong, in 2008, and the M.s. and ph.D. degrees in industrial Engineering from the University oflowa, lowa City, USA, in 2009 and 2012, respectively. His is currently Professor and Head of Department of Data Science at City University of Hong kong, Hong Kong, China. His research focuses on machine learning and computational intelligence methods as well as their applications in the renewable energy, facility energy management, rail transportation systems, and manufacturing processes. He is a senior member of IEEE. He is currently serving as an Associate Editor for IEEE Transactions on Sustainable Energy, IEEE Power Engineering Letters, and Journal of inteligent Manufacturing, as well as the advisory board member of Patterns: Cell Press.

Co-chair: Dr. Xin Liu, Beijing Institute of Technology, China

Xin Liu received a B.Eng. degree in industrial engineering from Beijing Institute of Technology in 2016, and a Ph.D. degree in data science from the City University of Hong Kong, Hong Kong SAR, China in 2021. He was an exchange student at the School of Mechanical Engineering, Karlsruhe Institute of Technology, Germany in 2016. He is currently an Assistant Professor with the School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China. His research interests include data science and optimization with applications in intelligent manufacturing, renewable energy, and product design.

Call for Papers Timeline / 征稿时间

  • Submission of Full Paper: March 10th, 2025
    投稿截止日: 2025年3月10日 

  • Notification Deadline: March 30th, 2025
    通知书发送: 2025年3月30日 

  • Registration Deadline: April 10th, 2025
    注册截止日期: 2025年4月10日