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Reference : UMR8029-ANNBLA-002
Workplace : BRUZ
Date of publication : Friday, June 26, 2020
Type of Contract : FTC Scientist
Contract Period : 12 months
Expected date of employment : 15 October 2020
Proportion of work : Full time
Remuneration : Between 2700€ and 3100€ monthly gross (according to CNRS payscale)
Desired level of education : PhD
Experience required : Indifferent
The proposed research work will consist in conducting optimisation studies regarding the optimal energy management in real-time of a large-scale smart grid, including a high number of electric vehicles for which traditional methods lead to a prohibitive computing time. The post-doctoral researcher will have to extend an existing multi-agents code developed with Python and Java, and coupled to power system simulator PowerFactory, to define simulation scenarios, and to optimise this system. Deterministic studies, but also stochastic studies, are envisaged. In addition, integrating learning capacities (ex: through methods such as deep learning) for the multi-agent system may also be envisaged.
The post-doctoral researcher's activities will be the following:
- scientific literature review
- extending an existing multi-agent code developed with Python and Java
- defining simulation scenarios and performing these simulations using power system simulator PowerFactory
- results analysis with Matlab
- participating and presenting the work in international and national conferences and seminars
- potentially, depending on the recruited candidate: conducting comparative optimisation studies at smaller scale using traditional methods (e.g. MILP) and tools (e.g. Gurobi).
- potentially, supervising Master 1 and Master 2 interns
The candidate should hold a PhD (or equivalent) in computer science, applied mathematics, numerical modeling, or electrical engineering with a strong interest in applied mathematics and programming.
Knowledge in object-oriented programming, as well as in Java or Python is required. An experience or background in optimization would be highly appreciated, as well as knowledge on learning techniques (such as deep learning). In addition, strong analytical thinking skills and critical thinking capabilities are required, and teamwork skills would be appreciated.
An interest in smart grids and renewables grid integration would be a plus.
The post-doctoral position will be located in SATIE, ENS Rennes. Occasional short stays in the Institut de Recherche en Informatique de Toulouse (IRIT) are planned.
Constraints and risks
The activities consist in numerical simulations on a computer.
This project is led in collaboration with EDF R&D and with the Institut de Recherche en Informatique de Toulouse (IRIT).
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