3 citations · 8 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
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…
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data
Mehmet Velioglu, Song Zhai, Sophia Rupprecht +3
In chemical engineering, process data are expensive to acquire, and complex phenomena are difficult to fully model. We explore the use of physics-informed neural networks (PINNs) f…
Nonlinear Manifold Learning Determines Microgel Size from Raman Spectroscopy
Eleni D. Koronaki, Luise F. Kaven, Johannes M. M. Faust +2
Polymer particle size constitutes a crucial characteristic of product quality in polymerization. Raman spectroscopy is an established and reliable process analytical technology for…
Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimization
Daniel Mayfrank, Na Young Ahn, Alexander Mitsos +1
Mechanistic dynamic process models may be too computationally expensive to be usable as part of a real-time capable predictive controller. We present a method for end-to-end learni…