Post-doctoral researcher in decentralised optimised energy management in smart grids M/W

Job title: Post-doctoral researcher in decentralised optimised energy management in smart grids M/W


Location: Bruz, Ille-et-Vilaine

Job Description: Offer Description

In order to integrate more and more renewable energy, the power system is being transformed into a smart grid. However, this transition will require shifting from a centralized management of flexible entities (power sources (e.g. PV, etc.), electric vehicles, …) to a highly decentralized, smart and dynamic energy management. It will also require considering a large number of flexible entities, multiple sources of uncertainties, constraints in the electrical network, etc. This represents a very complex problem that conventional methods are not able to address. In this context, there is a clear need for research works contributing actively to the development of decentralised energy management strategies for large-scale smart grids under uncertainty.

Some methods have been used on related, but only small-scale problems (up to 50 flexible entities [Pacaud2018]) as a greater number would lead to an explosion of the required computing time. On the contrary, methods based on multi-agent systems may present high scalability capabilities which render them particularly suitable for the real-time operational management of large-scale smart grids [Rizk2018]. In this perspective, research works are already being conducted in collaboration between SATIE, IRIT and Orange Labs on the problem considered here, and for which promising results have already been obtained [Zafar2023].

A project is led on this topic by Anne Blavette (CNRS researcher at ENS Rennes, belonging to the SATIE lab until 31/12/23, and with IETR lab from 01/01/24), in collaboration, among others, with the Institut de Recherche en Informatique de Toulouse. This project, entitled “EDEN4SG” is funded by the French National Research Agency (Agence Nationale de la Recherche (ANR)).

As part of this project, a post-doctoral researcher will have to develop fast power system models to accelerate the learning of near-optimal (dis)charging strategies from EVs. He/she will also have to apply the method developed to wind energy.

The position will include the following non-exhaustive list of tasks:

– Bibliographical search in the scientific literature
– Mathematical formalization of the considered scientific problems
– Numerical simulations (code development, testing and validation, experimentation, results discussion)
– Regular reporting to the supervising team
– Scientific publication writing
– Participation on local, national and international conferences and seminars

Teaching assignments at ENS will also be proposed.

The post-doc will be carried out mainly at ENS Rennes, with visits to IRIT in Toulouse.


Research Field Engineering Education Level PhD or equivalent

Research Field Physics Education Level PhD or equivalent

Research Field Technology Education Level PhD or equivalent

Languages FRENCH Level Basic

Research Field Engineering Years of Research Experience 1 – 4

Research Field Physics Years of Research Experience 1 – 4

Research Field Technology Years of Research Experience 1 – 4

Additional Information

Eligibility criteria

Doctor in the field of machine learning, applied mathematics, statistics, computer science or electrical engineering with a strong multi-disciplinary background.

Good programming skills on object-oriented programming would be highly appreciated (especially Python).

A strong capability to work in a team and communicate within a multidisciplinary team, both onsite and at a distance, would be very appreciated.

Knowledge on renewables, smart grids and energy storage would be a plus.

Additional comments

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Work Location(s)

Number of offers available 1 Company/Institute Systèmes et Applications des Technologies de l’Information et de l’Energie Country France City BRUZ Geofield

Where to apply Website

Contact City

BRUZ Website



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