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20242026
most citedPartially Observable Residual Reinforcement Learning for PV-Inverter-Based Voltage Control in Distribution Grids

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

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

Physics-Informed Neural Network for Modeling the Dynamic Behavior of Grid-Forming Converters

Hussein Jaffal, Arianna Fois, Sarra Bouchkati +2

This paper investigates physics-informed neural networks for modeling the full dynamic behavior of droop-controlled grid-forming converters. The approach is trained on synthetic da…

eess.SY2026

Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids

Josef Hoppe, Sarra Bouchkati, Farah Nasr +7

Increases in photovoltaic generation, charging of electric vehicles and heat-pump demand challenge operating limits in low-voltage distribution grids. This requires curative curtai…

eess.SY2025★ 1 cited

Partially Observable Residual Reinforcement Learning for PV-Inverter-Based Voltage Control in Distribution Grids

Sarra Bouchkati, Ramil Sabirov, Steffen Kortmann +1

This paper introduces an efficient Residual Reinforcement Learning (RRL) framework for voltage control in active distribution grids. Voltage control remains a critical challenge in…

cs.LG2024

End-to-End Reinforcement Learning of Curative Curtailment with Partial Measurement Availability

Hinrikus Wolf, Luis Böttcher, Sarra Bouchkati +9

In the course of the energy transition, the expansion of generation and consumption will change, and many of these technologies, such as PV systems, electric cars and heat pumps, w…