Central Queensland University, Australia
Prof. Jamshid Aghaei is a researcher and academic in renewable and sustainable energy systems, serving as a professor at the School of Engineering and Technology, Central Queensland University, Australia. As a Senior Member of IEEE, his work focuses on advancing decarbonised, digitalised, decentralised, and democratised power and energy systems, including smart grids, power system operation and planning, distributed energy integration, electricity markets, optimisation, AI, and data analytics. He has contributed to over 300 publications and more than 20 national and international research projects. His work has been recognised with an h-index of 77 and over 17,000 citations, and he has been listed among the top 2% of researchers worldwide by Stanford University. Prof. Aghaei places great value on mentoring the next generation of researchers, having guided more than 50 master’s students, 30 Ph.D. students, and 3 postdoctoral researchers. He also contributes to the academic community as an editor and associate editor for several respected journals, including IEEE Transactions on Smart Grid, IEEE Transactions on Cloud Computing, IEEE Systems Journal, IEEE Open Access Journal of Power and Energy, Electric Power System Research, and IET journals.
Extreme weather events such as floods and cyclones are no longer rare disturbances to electricity systems; they are increasingly defining operational and planning conditions. This keynote speech examines how power distribution networks can be designed to remain adaptive, resilient, and rapidly recoverable when extreme events simultaneously disrupt electrical and transportation infrastructures. The discussion adopts a data-driven and spatially informed perspective. Historical information from electricity distribution systems and regional transportation networks is synthesised to understand how past events have affected infrastructure performance and accessibility. Using GIS-based analysis, spatial vulnerability patterns are identified, highlighting locations where service disruption, access constraints, and critical demand intersect. These insights support targeted resilience strategies rather than broad, reactive interventions. Building on this foundation, the speech introduces the concept of Green Mobile Energy Hubs (GMEHs) as flexible, deployable resources for enhancing resilience. Advanced optimisation frameworks are presented to allocate GMEHs in disaster-prone areas and to route GMEH within each cluster for each scenario. In the allocation phase, stochastic and robust optimisation techniques explicitly account for uncertainty in hazard occurrence and system conditions, enabling proactive positioning of mobile energy assets. To this end, an algorithm based on Nearest Neighbour Routing and Dijkstra methods is developed. In the routing phase, real-time system status and accessibility information are incorporated to dynamically route GMEHs using shortest-path algorithms, minimising restoration time to critical loads. The algorithm is called Scenario-Adaptive Shortest-Path Greedy, and based on this framework, different methods for incorporating load priority are included.
University of Chinese Academy of Sciences, China
BIO: TBA
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