3 citations · 3 across the 7 of their papers we have counts for
12 papers
Emission-Aware Optimization of Gas Networks: Input-Convex Neural Network Approach
Vladimir Dvorkin, Samuel Chevalier, Spyros Chatzivasileiadis
Gas network planning optimization under emission constraints prioritizes gas supply with the least CO intensity. As this problem includes complex physical laws of gas flow, sta…
Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations
Robert I. Hamilton, Jochen Stiasny, Tabia Ahmad +5
Interpretable Machine Learning (IML) is expected to remove significant barriers for the application of Machine Learning (ML) algorithms in power systems. This letter first seeks to…
Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment
Alyssa Kody, Samuel Chevalier, Spyros Chatzivasileiadis +1
Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power f…
Uncertainty Quantification in LV State Estimation Under High Shares of Flexible Resources
Nils Müller, Samuel Chevalier, Carsten Heinrich +2
The ongoing electrification introduces new challenges to distribution system operators (DSOs). Controllable resources may simultaneously react to price signals, potentially leading…
Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation
Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis
In order to drastically reduce the heavy computational burden associated with time-domain simulations, this paper introduces a Physics-Informed Neural Network (PINN) to directly le…
Handling Initial Conditions in Vector Fitting for Real Time Modeling of Power System Dynamics
Tommaso Bradde, Samuel Chevalier, Marco De Stefano +2
This paper develops a predictive modeling algorithm, denoted as Real-Time Vector Fitting (RTVF), which is capable of approximating the real-time linearized dynamics of multi-input…