53 citations · 70 across the 6 of their papers we have counts for
6 papers
A Comparative Study of Graph Representations for GNN-Based Power Grid Control in L2RPN
Adrian Degenkolb, Qiong Huang, Benjamin Schäfer
Graph construction is a critical but underexamined design choice in deep reinforcement learning for power grid control. We present a controlled experimental comparison of different…
Graph Machine Learning: An Opportunity for Power Systems
Martin Sadric, Sebastian Pütz, Christian Nauck +4
Modern power systems face growing operational complexity driven by the integration of renewable energy sources, decentralization, and the need for real-time decision-making across…
A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods
Matthias Hertel, Sebastian Pütz, Jonathan Kolar +3
Accurate load forecasting at multiple grid levels is essential for future smart grids, ranging from aggregated control area forecasts for balancing supply and demand to forecasts o…
Regulatory Changes in Power Systems Explored with Explainable Artificial Intelligence
Sebatian Pütz, Johannes Kruse, Dirk Witthaut +2
A stable supply of electrical energy is essential for the functioning of our society. Therefore, the electrical power grid's operation and energy and balancing markets are subject…
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI
Sebastian Pütz, Benjamin Schäfer, Dirk Witthaut +1
The energy transition introduces more volatile energy sources into the power grids. In this context, power transfer between different synchronous areas through High Voltage Direct…
Wind Power Persistence Characterized by Superstatistics
Juliane Weber, Mark Reyers, Christian Beck +4
Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or o…