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20242026
most citedOptimizing Flexibility in Power Systems by Maximizing the Region of Manageable Uncertainties

3 citations · 8 across the 13 of their papers we have counts for

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math.OC2026

Robust Design of Multi-Energy Systems Accounting for Mixed-Integer Operational Problems

Moritz Wedemeyer, Alexander Mitsos, Manuel Dahmen

Identifying robust designs for multi-energy systems is computationally challenging. As rigorous approaches are often computationally intractable, heuristics are employed to generat…

math.OC2025

Accelerating Deterministic Global Optimization via GPU-parallel Interval Arithmetic

Hongzhen Zhang, Tim Kerkenhoff, Neil Kichler +4

Spatial Branch and Bound (B&B) algorithms are widely used for solving nonconvex problems to global optimality, yet they remain computationally expensive. Though some works have bee…

math.OC2025★ 1 cited

Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do?

Anastasia Georgiou, Daniel Jungen, Luise Kaven +4

Bayesian Optimization (BO) with Gaussian Processes relies on optimizing an acquisition function to determine sampling. We investigate the advantages and disadvantages of using a de…

math.OC2024★ 3 cited

Optimizing Flexibility in Power Systems by Maximizing the Region of Manageable Uncertainties

Aron Zingler, Stephane Fliscounakis, Patrick Panciatici +1

Motivated by the increasing need to hedge against load and generation uncertainty in the operation of power grids, we propose flexibility maximization during operation. We consider…

math.OC2024

Robust Energy System Design via Semi-infinite Programming

Moritz Wedemeyer, Eike Cramer, Alexander Mitsos +1

Time-series information needs to be incorporated into energy system optimization to account for the uncertainty of renewable energy sources. Typically, time-series aggregation meth…