no code implementations • 10 Dec 2023 • Antoine Marot, David Rousseau, Zhen Xu
Organising an AI challenge does not end with the final event.
1 code implementation • 3 Apr 2023 • Malte Lehna, Jan Viebahn, Christoph Scholz, Antoine Marot, Sven Tomforde
In this article, we analyse the submitted agent from Binbinchen and provide novel strategies to improve the agent, both for the RL and the rule-based approach.
1 code implementation • 21 Jul 2022 • Gaëtan Serré, Eva Boguslawski, Benjamin Donnot, Adrien Pavão, Isabelle Guyon, Antoine Marot
Current rapid changes in climate increase the urgency to change energy production and consumption management, to reduce carbon and other green-house gas production.
no code implementations • 21 Oct 2021 • Antoine Marot, Benjamin Donnot, Karim Chaouache, Adrian Kelly, Qiuhua Huang, Ramij-Raja Hossain, Jochen L. Cremer
We first advance an agent with the ability to send to the operator alarms ahead of time when the proposed actions are of low confidence.
no code implementations • 2 Mar 2021 • Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aïdan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero
Motivated to investigate the potential of AI methods in enabling adaptability in power network operation, we have designed a L2RPN challenge to encourage the development of reinforcement learning solutions to key problems present in the next-generation power networks.
no code implementations • 21 Dec 2020 • Loïc Omnes, Antoine Marot, Benjamin Donnot
We propose a new adversarial training approach for injecting robustness when designing controllers for upcoming cyber-physical power systems.
no code implementations • 3 Dec 2020 • Antoine Marot, Alexandre Rozier, Matthieu Dussartre, Laure Crochepierre, Benjamin Donnot
There is a great need for rethinking the human-machine interface under more unified and interactive frameworks.
1 code implementation • NeurIPS 2020 • Balthazar Donon, Zhengying Liu, Wenzhuo LIU, Isabelle Guyon, Antoine Marot, Marc Schoenauer
This paper introduces Deep Statistical Solvers (DSS), a new class of trainable solvers for optimization problems, arising e. g., from system simulations.
no code implementations • 26 Nov 2020 • Medha Subramanian, Jan Viebahn, Simon H. Tindemans, Benjamin Donnot, Antoine Marot
The behaviour of this agent is tested on different time-series of generation and demand, demonstrating its ability to operate the grid successfully in 965 out of 1000 scenarios.
no code implementations • 16 Mar 2020 • Adrian Kelly, Aidan O'Sullivan, Patrick de Mars, Antoine Marot
This paper presents the background material required for the Learning to Run Power Networks Challenge.
no code implementations • 5 Dec 2019 • Antoine Marot, Benjamin Donnot, Camilo Romero, Luca Veyrin-Forrer, Marvin Lerousseau, Balthazar Donon, Isabelle Guyon
For power grid operations, a large body of research focuses on using generation redispatching, load shedding or demand side management flexibilities.
1 code implementation • 22 Aug 2019 • Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer
We propose a novel neural network embedding approach to model power transmission grids, in which high voltage lines are disconnected and reconnected with one-another from time to time, either accidentally or willfully.
no code implementations • IJCNN 2019 • Balthazar Donon, Benjamin Donnot, Isabelle Guyon, Antoine Marot
Load flow computation is a well studied and understood problem, but current methods (based on Newton-Raphson) are slow.
no code implementations • 3 May 2018 • Benjamin Donnot, Isabelle Guyon, Antoine Marot, Marc Schoenauer, Patrick Panciatici
We address the problem of maintaining high voltage power transmission networks in security at all time, namely anticipating exceeding of thermal limit for eventual single line disconnection (whatever its cause may be) by running slow, but accurate, physical grid simulators.
no code implementations • 3 May 2018 • Benjamin Donnot, Isabelle Guyon, Marc Schoenauer, Antoine Marot, Patrick Panciatici
We evaluate that our method scales up to power grids of the size of the French high voltage power grid (over 1000 power lines).
1 code implementation • 30 Jan 2018 • Benjamin Donnot, Isabelle Guyon, Marc Schoenauer, Antoine Marot, Patrick Panciatici
We propose a new method to efficiently compute load-flows (the steady-state of the power-grid for given productions, consumptions and grid topology), substituting conventional simulators based on differential equation solvers.
no code implementations • 13 Nov 2017 • Antoine Marot, Sami Tazi, Benjamin Donnot, Patrick Panciatici
The segmentation of large scale power grids into zones is crucial for control room operators when managing the grid complexity near real time.
no code implementations • 27 Sep 2017 • Benjamin Donnot, Isabelle Guyon, Marc Schoenauer, Patrick Panciatici, Antoine Marot
One of the primary goals of dispatchers is to protect equipment (e. g. avoid that transmission lines overheat) with few degrees of freedom: we are considering in this paper solely modifications in network topology, i. e. re-configuring the way in which lines, transformers, productions and loads are connected in sub-stations.