activity
20202026
most citedModelling of Variable-Speed Refrigeration for Fast-Frequency Control in Low-InertiaSystems

11 citations · 14 across the 9 of their papers we have counts for

collaborators

10 papers

eess.SY2026

RAPTOR: RAndom-projection Physics-informed Transient sOlveR

Petros Ellinas, Benjamin Vilmann, Spyros Chatzivasileiadis +1

The complexity of time-domain simulation of modern power systems has increased significantly because converter-based resources introduce control dynamics that must be simulated alo…

eess.SY2026

Safety Screening for Voltage Control in Active Distribution Grids via Distributionally Robust Conformal Screening

Sarra Bouchkati, Petros Ellinas, Adriana Geisler +4

Deploying a new control policy for voltage control in active distribution grids requires evidence that physical limits will be satisfied before the policy is tested on the physical…

eess.SY2026

Multi-Objective Deep Reinforcement Learning for Secure and Stable Power System Operation

Ioannis Papadopoulos, Georgios Tsaousoglou, Johanna Vorwerk

The ongoing energy transition challenges the stable operation of power systems and increases the need for rapid decision-making under uncertainty. While reinforcement learning has…

cs.CE2026

Tools to Explain Neural Networks for Power System Dynamics

Petros Ellinas, Johanna Vorwerk, Spyros Chatzivasileiadis

This paper presents, for the first time in power systems literature to our knowledge, analytical tools to explain the training performance of machine learning surrogate models for…

eess.SY2026

Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation

Petros Ellinas, Indrajit Chaudhuri, Johanna Vorwerk +1

Physics-informed machine learning surrogates are increasingly explored to accelerate dynamic simulation of generators, converters, and other power grid components. The key question…

eess.SY2025

Neural Operators for Power Systems: A Physics-Informed Framework for Modeling Power System Components

Ioannis Karampinis, Petros Ellinas, Johanna Vorwerk +1

Modern power systems require fast and accurate dynamic simulations for stability assessment, digital twins, and real-time control, but classical ODE solvers are often too slow for…

eess.SY2025

Neural Networks for AC Optimal Power Flow: Improving Worst-Case Guarantees during Training

Bastien Giraud, Rahul Nellikkath, Rahul Nellikath +3

The AC Optimal Power Flow (AC-OPF) problem is central to power system operations but remains computationally challenging to solve due to its non-convex, nonlinear nature. Neural ne…

eess.SY2025

A Dataset Generation Toolbox for Dynamic Security Assessment: On the Role of the Security Boundary

Bastien Giraud, Lola Charles, Agnes Marjorie Nakiganda +2

Dynamic security assessment (DSA) is crucial for ensuring the reliable operation of power systems. However, conventional DSA approaches are becoming intractable for future power sy…

eess.SY2022★ 3 cited

Using Quantile Forecasts for Dynamic Equivalents of Active Distribution Grids under Uncertainty

Johanna Vorwerk, Thierry Zufferey, Petros Aristidou +1

While distribution networks (DNs) turn from consumers to active and responsive intelligent DNs, the question of how to represent them in large-scale transmission network (TN) studi…

eess.SY2020★ 11 cited

Modelling of Variable-Speed Refrigeration for Fast-Frequency Control in Low-InertiaSystems

Johanna Vorwerk, Uros Markovic, Petros Aristidou +2

In modern power systems, shiftable loads contribute to the flexibility needed to increase robustness and ensure security. Thermal loads are among the most promising candidates for…