AI and Data Driven New Energy Systems
Energy systems today are increasingly featured by new elements with high level of uncertainty from either renewable resources or from the latency introduced from the communications system. The complexity involved with multiple energy sources and interaction for both energy and ICT networks has introduced high level of difficulties for accurate modelling and thus control of the system. Conventional simulation based methods can be either computationally expensive or inaccurate due to modelling defects. With recent development in artificial intelligence, especially on deep learning technologies and other data based methodologies, new approaches for energy system operations and energy market opportunities have appeared. In this talk, some key issues, challenges and methodologies for new energy system and market operations will be introduced. Advanced data analytics and artificial intelligence for research, and case studies with real market data will be presented as well.
Professor Z.Y. Dong obtained Ph.D. from the University of Sydney, Australia in 1999. He is Director of ARC Research Hub on Integrated Energy Storage at the University of NSW, Sydney. His immediate role is Professor and Head of the School of Electrical and Information Engineering, The University of Sydney. He was Ausgrid Chair and Director of the Ausgrid Centre for Intelligent Electricity Networks (CIEN) providing R&D support for the $600M Smart Grid, Smart City national demonstration project. He also worked as manager for (transmission) system planning at Transend Networks (now TASNetworks), Australia. His research interest includes smart grid, power system planning, power system security, load modeling, renewable energy systems, and electricity market. He is an editor of IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, IEEE PES Transaction Letters and IET Renewable Power Generation. He is an international Advisor for the journal of Automation of Electric Power Systems. He is Fellow of IEEE.