10 papers
PF: A Benchmark Dataset for Power Flow under Load, Generation, and Topology Variations
Ana K. Rivera, Anvita Bhagavathula, Alvaro Carbonero +1
Power flow (PF) calculations are the backbone of real-time grid operations, across workflows such as contingency analysis (where repeated PF evaluations assess grid security under…
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…
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…
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…
Application-Driven Innovation in Machine Learning
David Rolnick, Alan Aspuru-Guzik, Sara Beery +8
In this position paper, we argue that application-driven research has been systemically under-valued in the machine learning community. As applications of machine learning prolifer…
Strategic bid response under automated market power mitigation in electricity markets
Chiara Fusar Bassini, Jacqueline Adelowo, Priya L. Donti +1
In auction markets that are prone to market power abuse, preventive mitigation of bid prices can be applied through automated mitigation procedures (AMP). Despite the widespread ap…