Special Session One
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Session Title: Next-Generation Computational Engines for Power System Applications: Quantum Computing, AI, and Beyond
Modern power systems are becoming increasingly complex due to the rapid growth of renewable energy integration, distributed energy resources, electrified transportation, and sector coupling. These developments are transforming the scale, uncertainty, temporal dynamics, and cyber-physical interactions of power systems, thereby imposing unprecedented requirements on system modeling, optimization, control, security assessment, and market operation. Conventional computational approaches, while still essential, are facing growing challenges in coping with the scale, nonlinearity, uncertainty, and real-time requirements of emerging power system applications.
Against this background, next-generation computational engines are attracting increasing attention as promising enablers for future power system analysis and operation. These engines include, but are not limited to, quantum computing, quantum-inspired optimization, artificial intelligence, large language models, and other advanced computational paradigms. They offer new opportunities to improve computational efficiency, decision quality, adaptability, and scalability in a wide range of power system problems.
This special session aims to provide a dedicated platform for researchers, academics, and industry practitioners to exchange the latest advances in next-generation computational methods for power system applications. It seeks to promote interdisciplinary interaction between the power and energy community and researchers in advanced computing, data science, and intelligent systems. Contributions are welcome on topics including, but not limited to, quantum and quantum-inspired optimization for grid operation, learning-enhanced power system modeling and control, AI-based stability and security assessment, computational intelligence for renewable integration, next-generation computing for electricity markets and planning, edge intelligence for distributed energy management, trustworthy and explainable computational methods, and benchmark studies for advanced computational engines in energy systems. Both methodological innovations and application-oriented studies are encouraged to support the development of more capable, efficient, and resilient future power systems.
Special Session Chairs
Yateendra Mishra
Queensland University of Technology, Australia
Yateendra Mishra (Senior Member, IEEE) received his B.E. degree in Electrical and Electronics Engineering from Birla Institute of Technology (BIT), Mesra, India, in 2003; M.Tech. degree in Energy Studies from Indian Institute of Technology Delhi (IITD), New Delhi, India, in 2005; and Ph.D. degree in Electrical Engineering from The University of Queensland (UQ), Brisbane, Qld., Australia, in 2009.
He was a visiting Scholar in The University of Tennessee, Knoxville, TN, USA, in 2009 and worked as a Transmission Planning Engineer with Midwest ISO, IN, USA from 2009-2011. He joined Queensland University of Technology (QUT), Brisbane, Qld., Australia in Jul 2011 as a Lecturer and is currently an associate professor in power engineering. He was a visiting researcher at Illinois Institute of Technology, Chicago, IL, USA, in June 2014.
His current research interests include Demand Response and Demand Aggregators; Power System Planning; Transmission and Generation Interconnection, Electricity Markets, DER Operation and Management, Power System Stability and Control.
Dr. Mishra is an Advance Queensland Fellow and a member of ANC-CIGRE.
Yuchen Zhang
Queensland University of Technology, Australia
Yuchen Zhang (Member, IEEE) received the B.E., B.Com., and Ph.D. degrees from the University of NewSouth Wales, Sydney, NSW, Australia, in 2013, 2013, and 2018, respectively. He is currently a Lecturer and an ARC Discovery Early Career Researcher Award Fellow with the School of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD, Australia. He was a Research Associate with the ARC Research Hub for Integrated Energy Storage Systems, University of New South Wales, Sydney, NSW, Australia. His research interests include power system stability assessment and control, wind farm planning, condition monitoring, smart campus, and data-driven applications in power systems.
Robert Marlin
Queensland University of Technology, Australia
Robert Marlin (Member, IEEE; Member, IEEE Power & Energy Society) received his Ph.D. from the Queensland University of Technology (QUT), Brisbane, QLD, Australia. He is currently affiliated with the School of Electrical Engineering and Robotics at QUT and has also undertaken teaching and research support roles across the university.
His research interests include post-quantum cryptography for cyber-physical energy systems, secure communications for electric vehicles and distributed energy resources, federated and privacy-preserving learning, and intelligent energy management systems. His recent work focuses on the evaluation of post-quantum secure communication frameworks for grid-connected home energy management systems, electric vehicle infrastructure, and distributed energy environments under realistic operational and cyber-security conditions.
Dr Marlin has contributed to research in advanced computational and security methodologies for future energy systems, with interests spanning quantum-resistant communication architectures, distributed optimisation, and AI-enabled energy applications.