The production of green hydrogen through electrolysis is one of the relevant solutions for decarbonization and energy sustainability. However, it faces major challenges related to the variability of renewable energy sources such as wind and solar. This variability can accelerate the degradation of electrolyzers, increasing production costs and reducing their lifespan. To ensure competitive production of decarbonized hydrogen, it is essential to find a balance between the optimal use of decarbonized electricity and the maximization of electrolyzer operating time.

Recent studies, such as those by Y. Li et al. [1] and J. Wang et al. [2], have explored control strategies to optimize hydrogen production from renewable energies. Additionally, approaches based on artificial intelligence, such as those by J. Li et al. [3] and Yadollahi et al. [4], have shown their effectiveness in managing energy systems.

Within a team composed of about twenty experts (hydrogen systems modeling, operations research, machine learning, programming), this post-doctoral project will focus on demonstrating the feasibility and relevance of intelligent control strategies to reduce system degradation while optimizing green hydrogen production.

Your missions will be:

• Toconduct a literature research and interviewswith other CEA research in order to refine the definition of the envisioned case study with relevant parameters and data.
• Tocreate a simulation modelfor the case study, which should be based on existing component models [5], and should include relevant reference control strategies to serve as a benchmark.
• Todesign and implement new control strategiesbased on machine learning and reinforcement learning algorithms to optimize the control of electrolyzers. These control strategies will be designed to reduce electrolyzer degradation, maximize energy efficiency and minimize production costs.
• Toperform an in-depth analysis and comparisonof possible control strategies on the case study, especially focusing on their performance regarding electrolyzer degradation.
• Topublish results in scientific journalsand contribute to cooperation with French and International academics. Publication of some project results as Open Data and/or Open Source will also be possible.

The work will be conducted in a collaboration between teams located at the National Institute for Solar Energy (Le Bourget du Lac, Savoie), and at CEA LITEN in Grenoble. You will fully benefit from the dynamic working environment at CEA, including possibilities for scientific collaboration at the national and international level. The position is located in Le Bourget du Lac, with possibilities for partial remote work.