EURO 2025 Leeds
Abstract Submission

1572. Real-time optimization of distribution electricity network management

Invited abstract in session MD-44: Decentralized energy system integration modelling, stream Energy Economics & Management.

Monday, 14:30-16:00
Room: Newlyn 1.01

Authors (first author is the speaker)

1. Jean Jodeau
Sia AI
2. Saoussen Abidi
Data Science, Sia Partners
3. Tristan BASLER
Sia AI
4. Simon Bayle
Sia IA,
5. Nicolas Blandamour
Sia AI
6. Germain Francois
7. Paul Javal
Direction Technique, Enedis
8. Olav LAFOURCADE
R&D, Sia
9. Pierre Mordant
Sia AI
10. Lucas Selini
Sia AI

Abstract

The evolution of the role of DSOs, in particular ones involved in Active Network Management, requires strategic changes from historical monitoring and control approaches. DSOs must adapt to manage an increasing number of distributed energy resources, a growing number of planned worksites, while meeting regulatory and quality standards.
A first milestone in developing a decision support tool based on optimization and power flow management will be presented. It relies on an optimization model designed to mitigate electrical constraints, enhance network robustness while explicitly taking into account economic efficiency. The resulting optimal set of actions - flexibilities, power limitations, network reconfigurations - follow complex DSO operational rules.
A critical aspect of this work has been the collaboration with operators to build upon their knowledge and feedback. This engagement has been instrumental in identifying the several implicit industrial rules and best-practices. Leveraging black-box optimization methods and meta-heuristics, such as local search algorithms, the model provides operators with actionable insights and dispatching’s advice.
Future developments will focus on incorporating machine learning techniques to enhance convergence times and further optimize decision-making processes. By addressing these challenges and integrating operator expertise, this work supports the efficient operation of distribution networks and improve overall grid reliability

Keywords

Status: accepted

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