RESEARCH FIELDEnvironmental science › Earth science
RESEARCHER PROFILERecognised Researcher (R2)
APPLICATION DEADLINE09/05/2021 00:00 - Europe/Athens
LOCATIONFrance › Nantes
TYPE OF CONTRACTTemporary
HOURS PER WEEK38
OFFER STARTING DATE01/09/2021
IS THE JOB RELATED TO STAFF POSITION WITHIN A RESEARCH INFRASTRUCTURE?Yes
In 2018, in the document “Going Climate Neutral by 2050”, EU presents a long-term strategic vision to reduce greenhouse gas (GHG) emissions which outlines seven strategic blocks among which: 1) to maximize the deployment of renewables and 2) to develop smart networks infrastructure and interconnection. European energy transition targets a system with a share of 32% of renewable by 2030. However, the mismatch between energy availability and demand and the diffuse nature of renewable sources challenges this objective. Multi-carrier Energy Systems (MES) are foreseen as of the most promising ways to achieve an efficient integration of renewable energy sources in the future energy mix. Indeed, exploiting the synergy between different energy carriers improves the flexibility of the energy system and facilitates mitigating the mismatch between energy availability and demand. In these systems, the interaction between different energy carriers such as heat, electricity, gas, hydrogen, etc… can take place through interconnected energy networks at the building, regional, or national level. Designing and planning such networks are complex problems that require taking into account a large number of parameters including energy demand and its variability, energy resources availability and intermittence, energy and systems costs. Besides, these problems are also subject to multiple technical constraints related to the operation of the technologies used for energy production and storage, other constraints related to the energy networks used for transport and distribution, and additional constraints related to the environment or urban planning among others. Different research works aim to develop modelling tools to simulate the interactions between the components of large multi-carrier networks. Their combination with the optimization and decision aiding techniques is a solution to handle these complex problems. However, modelling tools that can simulate such large systems in reasonable computation times are lacking and continuous efforts are made by researchers around the world to develop new models and to imagine new methodologies to optimize large multi-carrier networks. In this context, researchers at IMT Atlantique develop continuously the software platform GEMELLUS for multi-carrier energy networks modelling and optimization. This platform combines innovative modelling and optimization approaches with HPC to tackle the complexity of these decision problems.
In this context the Post Doc will work on different demonstration use cases using the GEMELLUS platform to test the performance of the models and the optimization solutions developed by the team for optimal design and operation of MES. Working on these practical use cases aims to identify possible improvements the Post Doc will be in charge of addressing. He/She will also participate to the ongoing development of additional functionalities of both modelling solutions and optimization strategies, together at the energy systems scale and the distribution networks level.
REQUIRED LANGUAGESFRENCH: GoodENGLISH: Excellent
The candidate should have obtained a PhD in the field of Energy
engineering or Applied Mathematics with experience in the Energy field.
He/She will have strong skills in energy systems modelling with a proven
experience in the development of models of one or many energy systems
(production/ conversion/storage/transport etc..). Excellent mastery of
scientific programming and algorithmic will be a very important
selection criterion. Good knowledge of optimization algorithms is
strongly recommended. The candidate will demonstrate the English level
compatible with daily work in an international context added to
excellent teamwork competencies.
EURAXESS offer ID: 621510
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