15 papers
Learning Discrete Decisions for MIPs with Constraint-Aware Diffusion
Vincenzo Di Vito, Mehdi Taghizadeh, Deepjyoti Deka +2
This paper proposes a novel learning-based approach to approximately solve instances of mixed-integer optimization problems. These problems are computationally challenging, as they…
Strategic Spatial Load Shifting and Market Efficiency
Aron Brenner, Deepjyoti Deka, Line Roald +1
Large, spatially flexible electricity consumers such as data centers can reallocate demand across locations, influencing dispatch and prices in wholesale electricity markets. While…
Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk
Parikshit Pareek, Sidhant Misra, Deepjyoti Deka
The absence of formal performance guarantees in machine learning (ML) has limited its adoption for safety-critical power system applications, where confidence and interpretability…
A Family of Convex Models to Achieve Fairness through Dispersion Control
Abhay Singh Bhadoriya, Deepjyoti Deka, Kaarthik Sundar
Controlling the dispersion of a subset of decision variables in an optimization problem is crucial for enforcing fairness or load-balancing across a wide range of applications. Bui…
Stability-Constrained AC Optimal Power Flow--A Gaussian Process-Based Approach
Vincenzo Di Vito, Kaarthik Sundar, Ferdinando Fioretto +1
The Alternating Current Optimal Power Flow (ACOPF) problem is a core task in power system operations, aimed at determining cost-effective generation dispatch while satisfying physi…
Equitable Routing--Rethinking the Multiple Traveling Salesman Problem
Abhay Singh Bhadoriya, Deepjyoti Deka, Kaarthik Sundar
The Multiple Traveling Salesman Problem (MTSP) extends the traveling salesman problem by assigning multiple salesmen to visit a set of targets from a common depot, with each target…