To meet the challenges and ambitions of TotalEnergies, the Hybrid and Storage R&D proposes solutions to optimize the sizing and operation of energy systems that couple multiple, often intermittent, energy sources for various applications. It also evaluates key performance indicators during the sizing phase and prepares for the commissioning phase of such projects. With the increasing complexity of new energy systems and the diversity of technologies, the OptimHYSe project aims to build a library of models for these technologies, with an in-depth analysis of their design and operation.

The objective of the internship is to benchmark different heuristic optimization methods (Genetic, PSO, EGO, etc.) and test them on concrete application cases. The idea is to understand which method is best suited to the various optimization problems faced by the OptimHYSe team. The expected deliverables at the end of this internship will be precise technical documentation of the different methods tested as well as a comparative study. The intern will also be required to code/integrate various functionalities into the current framework.

Your role will consist of:

• Benchmarking different heuristic algorithms and testing them on concrete cases
• Testing the dynamic parameterization of genetic/PSO parameters
• Better understanding which heuristic algorithm is best suited to each type of project

At the end of the mission, the following will be expected:

• Detailed sheets on the different heuristic methods
• Integration of dynamic parameterization for the PSO/genetic algorithm into the TTE framework code
• Comparison of the performance of heuristic methods on simple cases
• Documentation on the methodology for selecting the heuristic methods used

You will evolve within a team of experienced professionals and with a tutor-coach, the reference for your future profession. Individualized support will help you develop your autonomy and lead you to your diploma!

Currently enrolled in an engineering school or Master's program in the Operational research field, are you looking for an 6-month end-of-study internship starting in March 2025?

Do you have experience in computer science, operations research, energy systems, or a related field, knowledge of optimization techniques (e.g., MILP, MINLP, ...) and of renewable hybrid energy systems? Do you know Python for modeling and simulation, data analysis tools, and statistical software and libraries such as pyomo/pymoo?

Are you comfortable with office automation and familiar with the Office suite? You'll be using Excel, Word and Powerpoint in particular.

Are you a self-starter, rigorous and a team player? Can you take the initiative?

A professional command of French will be essential for this position. Written and oral communication skills for effective reports and presentations are a plus.

So don't wait any longer, apply to join our team!

Cette offre concerne un stage conventionné à temp plein, les stages alternés ne sont possibles.
 Pour postuler, merci de joindre un CV + lettre de motivation (vos dates de stage doivent être indiquées).

This offer is for a full-time, contractual internship; alternating internships are not possible.

To apply, please attach a CV + covering letter (your internship dates must be indicated).