Monday, October 28, 2024 - 4:00pm
Event Calendar Category
Other LIDS Events
Speaker Name
Yuanyuan Shi
Affiliation
University of California San Diego
Building and Room number
45-500A
Event Recording
"Learning for Power Grid and Building Control"
In this talk, I will share our recent progress on developing learning algorithms for real-world energy system control, with stability and computational tractability guarantees.
The first application is power grid voltage control. I will introduce a novel neural network architecture – monotone neural network (MNN) that ensure the network output is a monotone function of the input. MNN is achieved by first designing neural networks that are convex (with universal approximation guarantee) and using gradients of convex functions to ensure monotonicity. We show that MNN is a powerful structure for voltage control – with stability guarantee and superior performance compared to standard neural networks.
The second application is building control. There is an emergent need to model indoor air quality to improve occupant health and building energy efficiency. A fundamental challenge is that building airflow dynamics are governed by nonlinear partial differential equations (PDEs) with unknown parameters, which are computationally prohibitive from a real‑time control perspective. I will introduce our work on PDE‑constrained optimization for building model identification and designing neural operator learning for efficient PDE system control.
Yuanyuan Shi is an Assistant Professor at the Department of Electrical and Computer Engineering at the University of California San Diego. She received her Ph.D. in Electrical and Computer Engineering (ECE) from the University of Washington in 2020. From 2020 to 2021, she was a Postdoctoral Scholar at Caltech. Her research focuses on machine learning, dynamical systems and control, with applications to sustainable energy systems. She is a recipient of the Hellman Fellowship in 2023, the UW Clean Energy Institution Scientific Achievement Award in 2020, and best paper finalist from ACM e-Energy 2022.
The newly formed Energy Systems & Infrastructures: Modeling, Computing and Control (EIMC2) LIDS research group comprises 10 LIDS subgroups working in this field unique to LIDS–modeling, control, and computing. EIMC2 is launching a biweekly seminar series. The seminars will be help in 45-500A on Tuesdays, 4-5pm unless otherwise noted.
For any questions, please reach out to seminar organizers Rahman Khorramfar (khorram[at]mit[dot]edu) and Luis Carlos (luiscvm[at]mit[dot]edu)