Title: Addressing Uncertainty in Analysis and Design of Complex Renewable-Based Energy Systems

Abstract: Electric power systems are experiencing drastic transformations from centralized fossil-fuel-based generation to renewable and distributed energy resources (DERs). However, DERs are typically small in capacity and renewable generation is inherently variable, rendering hundreds of millions of uncertain control points. This transformation further exacerbates the complexity of power systems, which demands rigorous theoretical guarantees and efficient computational methods to ensure system robustness.

The uncertainty of renewable resources impacts power systems on multiple timescales. From the perspective of fast dynamics, the impacts of uncertainty need to be analyzed and quantified to guarantee safe and stable system operation. On the time horizon of long-term planning, it is essential to manage the uncertainty and properly design the system to balance investment cost and system reliability. In this talk, I will present my research which 1) addresses the critical issues of safety and stability of power systems that integrate substantial renewable DERs; 2) establishes a design process for next-generation multi-energy systems. I will conclude the talk by discussing promising research directions to facilitate a clean energy future, with a focus on dynamic analysis and safety certification of inverter-based smart grids.

Bio: Sijia Geng recently joined Laboratory for Information and Decision Systems at MIT as a postdoctoral associate. She received her Ph.D. in Electrical and Computer Engineering in January 2022 from the University of Michigan, Ann Arbor, where she also received the M.S. degrees in Mathematics and ECE, both in 2021. Before joining the University of Michigan, Sijia completed her B.E. degree in Automation at Harbin Institute of Technology, China, in 2016. Sijia’s research interests include analysis, control, and optimization of power and energy systems, with a focus on grid-integration of renewable resources and multi-energy systems. Sijia was the recipient of a Barbour Scholarship (University of Michigan) and has been selected as a participant in Rising Stars in EECS (MIT).