activity
20232026
most citedPartially Observable Residual Reinforcement Learning for PV-Inverter-Based Voltage Control in Distribution Grids

1 citations · 1 across the 4 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

Data-Driven Sequential Market Optimization for Front-of-the-Meter Battery Energy Storage Systems

Steffen Kortmann, Hannah Sanders, Andreas Ulbig

The growing integration of Battery Energy Storage Systems into electricity markets has highlighted the importance of coordinated participation across energy and balancing services…

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…

eess.SY2024

Safe Trajectory Sets for Online Operation of Power Systems under Uncertainty

Florian Klein-Helmkamp, Tina Möllemann, Irina Zettl +2

Flexibility provision from active distribution grids requires efficient and robust methods of optimization and control suitable to online operation. In this paper we introduce cond…

eess.SY2023

Representation of Distribution Grid Expansion Costs in Power System Planning

Luis Böttcher, Christian Fröhlich, Steffen Kortmann +3

The shift towards clean energy brings about notable transformations to the energy system. In order to optimally plan a future energy system, it is necessary to consider the influen…