Cover Image

Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lehna, Malte, Viebahn, Jan, Scholz, Christoph, Marot, Antoine, Tomforde, Sven
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fault Detection for agents on power grid topology optimization: A Comprehensive analysis
by: Lehna, Malte, et al.
Published: (2024)

HUGO -- Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach
by: Lehna, Malte, et al.
Published: (2024)

Superposition theorem for flexible grids
by: Marot, Antoine, et al.
Published: (2023)

Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach
by: Hassouna, Mohamed, et al.
Published: (2025)

Accelerated DC loadflow solver for topology optimization
by: Westerbeck, Nico, et al.
Published: (2025)

A Reinforcement Learning Approach for the Continuous Electricity Market of Germany: Trading from the Perspective of a Wind Park Operator
by: Lehna, Malte, et al.
Published: (2021)

Imitation Learning for Intra-Day Power Grid Operation through Topology Actions
by: de Jong, Matthijs, et al.
Published: (2024)

Online learning for robust voltage control under uncertain grid topology
by: Yeh, Christopher, et al.
Published: (2023)

Exact and Evolutionary Algorithms for Sequential Multi-Objective Transmission Topology Planning
by: Groeneveld, Job, et al.
Published: (2026)

Graph neural networks for power grid operational risk assessment under evolving grid topology
by: Zhang, Yadong, et al.
Published: (2024)

Avoidance of an unexpected obstacle without reinforcement learning: Why not using advanced control-theoretic tools?
by: Join, Cédric, et al.
Published: (2025)

Scalable spectral representations for multi-agent reinforcement learning in network MDPs
by: Ren, Zhaolin, et al.
Published: (2024)

Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
by: Duan, Yaqi, et al.
Published: (2024)

On learning racing policies with reinforcement learning
by: Czechmanowski, Grzegorz, et al.
Published: (2025)

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration
by: Ju, Caleb, et al.
Published: (2024)

A large synthetic dataset for machine learning applications in power transmission grids
by: Gillioz, Marc, et al.
Published: (2024)

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR
by: Syed, Shahbaz P Qadri, et al.
Published: (2025)

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
by: Åstrand, Teodor, et al.
Published: (2026)

An advanced robust integral reinforcement learning scheme with the fuzzy inference system
by: Ao Liu, et al.
Published: (2024)

Revisiting angle stability in power systems with grid-forming power converters
by: Ávila-Martínez, Régulo E., et al.
Published: (2026)

A reinforcement learning agent for maintenance of deteriorating systems with increasingly imperfect repairs
by: Marugán, Alberto Pliego, et al.
Published: (2025)

Equitably allocating wildfire resilience investments for power grids: The curse of aggregation and vulnerability indices
by: Pollack, Madeleine, et al.
Published: (2024)

Universal dual-port grid-forming control: bridging the gap between grid-forming and grid-following control
by: Subotić, Irina, et al.
Published: (2023)

Multi-Objective Reinforcement Learning for Power Grid Topology Control
by: Lautenbacher, Thomas, et al.
Published: (2025)

Defending the power grid by segmenting the EV charging cyber infrastructure
by: Kuroptev, Kirill, et al.
Published: (2026)

Comments on characterizing demand flexibility to provide power grid services
by: Barooah, Prabir
Published: (2024)

Enhancing power grid resilience to cyber-physical attacks using distributed retail electricity markets
by: Nair, Vineet Jagadeesan, et al.
Published: (2023)

Multi-agent assignment via state augmented reinforcement learning
by: Agorio, Leopoldo, et al.
Published: (2024)

Predicting power grid frequency dynamics with invertible Koopman-based architectures
by: Lupascu, Eric, et al.
Published: (2026)

Flowsheet synthesis through hierarchical reinforcement learning and graph neural networks
by: Stops, Laura, et al.
Published: (2022)

Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions
by: Marot, Antoine, et al.
Published: (2023)

Bellman Memory Units: A neuromorphic framework for synaptic reinforcement learning with an evolving network topology
by: Banerjee, Shreyan, et al.
Published: (2025)

Reinforcement Twinning: from digital twins to model-based reinforcement learning
by: Schena, Lorenzo, et al.
Published: (2023)

Research on image processing of electric power system terminals based on reinforcement learning and mobile edge computing optimization
by: Hui Zhou, et al.
Published: (2024)

Active-power control strategies in grid-forming power converters to improve transient stability in power systems with 100% converter-based generation
by: Ávila-Martínez, Régulo E., et al.
Published: (2026)

Distributed bilayered control for transient frequency safety and system stability in power grids
by: Zhang, Yifu, et al.
Published: (2019)

Towards adaptive trajectories for mixed autonomous and human-operated ships
by: Pianini, Danilo, et al.
Published: (2024)

Exploring the Dynamics of Data Transmission in 5G Networks: A Conceptual Analysis
by: Smirnov, Nikita, et al.
Published: (2024)

Dynamic state estimation of hybrid systems: Inverters that switch between grid-following and grid-forming control schemes
by: Odunlami, Bukunmi G., et al.
Published: (2025)

Networked dynamics with application to frequency stability of grid-forming power-limiting droop control
by: Iraniparast, Amirhossein, et al.
Published: (2024)