121 citations · 265 across the 19 of their papers we have counts for
22 papers
DCEmbed: Scalable Optimization over Neural Surrogates
Akshay Sreekumar, Nicolas Christianson, Priya L. Donti +2
Neural surrogates can accelerate large-scale optimization by replacing expensive or intractable model components with efficient learned approximations, but solving the resulting em…
Scalable Self-Supervised Learning for Multiphase AC-OPF in Distribution Systems with Topology Reconfiguration
Hoang T. Nguyen, Shaohui Liu, Reetam Sen Biswas +4
The proliferation of distributed energy resources (DERs) in distribution grids enables the active coordination of these assets to reduce costs and enable cleaner operations. Realiz…
Modeling of Network Constraints in Large-scale Capacity Expansion Optimization of Power Grids
Yu Weng, Lara Booth, Priya L. Donti +1
Capacity expansion modeling plays a critical role in optimizing the deployment of new generation, storage, and transmission, typically at national and regional levels. To support l…
Improving Feasibility via Fast Autoencoder-Based Projections
Maria Chzhen, Priya L. Donti
Enforcing complex (e.g., nonconvex) operational constraints is a critical challenge in real-world learning and control systems. However, existing methods struggle to efficiently en…
Optimization Under Uncertainty for Energy Infrastructure Planning: A Synthesis of Methods, Tools, and Open Challenges
Rahman Khorramfar, Aron Brenner, Lara Booth +4
Energy infrastructure planning under uncertainty has become increasingly complex as electrification, interdependence between energy carriers, decarbonization, and extreme weather e…
Cheap Thrills: Effective Amortized Optimization Using Inexpensive Labels
Khai Nguyen, Petros Ellinas, Anvita Bhagavathula +1
To scale optimization and simulation, prior work has explored training machine-learning surrogates that map problem parameters to solutions inexpensively at inference time. Unfortu…