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Santiago Grijalva
Southern Company Distinguished Professor, School of Electrical and Computer Engineering, College of Engineering, Georgia Institute of Technology
Speaker Biography:
Prof. Santiago Grijalva is the Southern Company Distinguished Professor of Electrical and Computer Engineering and Director of the Advanced Computational Electricity Systems (ACES) Laboratory at the Georgia Institute of Technology. His research interests include future electricity systems, decentralized power system control, and applications of machine learning. He has been principal investigator for numerous industry and Government research programs, published over 250 peer-reviewed papers, and managed $50 million in research grants . From 2013 to 2014 he served at the National Renewable Energy Laboratory (NREL) as founding Director of the Power System Engineering Center (PSEC). Dr. Grijalva has received multiple academic and professional awards and has served as a strategic advisor to Fortune 500 energy companies. He holds master's degrees in electrical engineering, information systems management, and data science. He obtained his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (2002), where he also completed a postdoctoral fellowship in Energy Systems (2004).
Abstract:
The electricity grid is undergoing a fundamental transformation driven by the integration of distributed energy resources (DERs), power electronics technologies, the emergence of prosumers, and advanced digital intelligence. Instead of centralized command-and-control, the emerging paradigm relies on decentralized control, optimization protocols, and learning methods, where decision-making is pushed closer to the edge to orchestrate millions of heterogeneous devices and actors in real time. Prosumers, equipped with inverter-based resources, digital connectivity, and intelligence, provide grid stabilization services that must be integrated seamlessly with power system operations. This talk presents the technical foundations of decentralized architectures and power coordination protocols, and describes how distributed optimization and AI can align safety, autonomy, scalability, sustainability, resilience, and economic efficiency objectives at massive scale, positioning the grid as an intelligent, participatory, and sustainable infrastructure for the future.