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20222026
most citedInterpretable Machine Learning Models for Modal Split Prediction in Transportation Systems

3 citations · 4 across the 8 of their papers we have counts for

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5 papers · 1 filter

eess.SY2026

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…

eess.SY2026

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…

eess.SY2025

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…

eess.SY2024

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…

eess.SY2024

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…