Controlling for Uncertainty
by A.J. Kleber
We live in an era of ever-increasing complexity and overwhelming choices, thanks to exploding technological advancement, which affect even the foundational systems that keep society functional. Critical energy infrastructure is increasingly impacted by volatile, variable use and demand, as individual customers respond to real-time information about pricing and service provider incentives. Meanwhile, the models and strategies that manage our power grids were designed for much more predictable conditions. An updated approach is needed in order to ensure robust, reliable service in the face of these inconsistencies, in addition to the booming energy demands made by AI and other advanced data processing and computation.
With the support of a $380K grant from the NSF, Professor Emiliano Dall’Anese is working to design the novel optimization methods required for complex infrastructures under these evolving conditions. His approach involves the development of algorithms and mathematical strategies which can adapt and account for real-time usage data, competing incentives from different service providers, and other factors, allowing for a responsive and nimble minute-by-minute management of resources to maintain smooth energy distribution. The resulting innovations will have potential applications in other, similarly complex systems, such as transportation networks.
Professor Emiliano Dall’Anese joined the BU ECE faculty in 2024. His accolades include a 2020 NSF CAREER Award, Best Paper Awards from IEEE ISGT Europe (2024) andIEEE Transactions on Control of Network Systems (2023), and the IEEE Power and Energy Society Prize Paper Award (2021). He received his Ph.D. at the University of Padova, Italy, in 2011.