3 citations · 4 across the 8 of their papers we have counts for
8 papers
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…
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…
Strategic Data Center Load Shifting: Implications for Market Efficiency and Transmission Value
Aron Brenner, Line Roald, Saurabh Amin
Data center electricity use may reach 12% of U.S. demand by 2030, alongside growing ability to shift workloads geographically in response to prices or carbon signals. We examine th…
A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
Aron Brenner, Rahman Khorramfar, Jennifer Sun +1
Two-stage adaptive robust optimization (ARO) is a powerful approach for planning under uncertainty, balancing first-stage decisions with recourse decisions made after uncertainty i…
Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian Optimization Approach
Aron Brenner, Rahman Khorramfar, Dharik Mallapragada +1
Solving large-scale capacity expansion problems (CEPs) is central to cost-effective decarbonization of regional-scale energy systems. To ensure the intended outcomes of CEPs, model…
Learning Spatio-Temporal Aggregations for Large-Scale Capacity Expansion Problems
Aron Brenner, Rahman Khorramfar, Saurabh Amin
Effective investment planning decisions are crucial to ensure cyber-physical infrastructures satisfy performance requirements over an extended time horizon. Computing these decisio…
Graph Representation Learning for Energy Demand Data: Application to Joint Energy System Planning under Emissions Constraints
Aron Brenner, Rahman Khorramfar, Dharik Mallapragada +1
A rapid transformation of current electric power and natural gas (NG) infrastructure is imperative to meet the mid-century goal of CO2 emissions reduction requires. This necessitat…
Interpretable Machine Learning Models for Modal Split Prediction in Transportation Systems
Aron Brenner, Manxi Wu, Saurabh Amin
Modal split prediction in transportation networks has the potential to support network operators in managing traffic congestion and improving transit service reliability. We focus…