Post-doctoral Research Visit F/m Strategies for

il y a 1 semaine


MontbonnotSaintMartin, Auvergne-Rhône-Alpes, France Inria Temps plein
Le descriptif de l'offre ci-dessous est en Anglais_

Type de contrat :

CDD

Contrat renouvelable :
Oui

Niveau de diplôme exigé :
Thèse ou équivalent

Fonction :
Post-Doctorant

A propos du centre ou de la direction fonctionnelle:

The Centre Inria de l'Université de Grenoble groups together almost 600 people in 22 research teams and 8 research support departments.


Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE,), but also with key economic players in the area.


The Centre Inria de l'Université Grenoble Alpes is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence.

The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.


Contexte et atouts du poste:

Working Context. This research will be conducted by the DANCE research team (webpage): DANCE ("Dynamics

Mission confiée:

Scientific Context. Our group has developed eMob-TwinV1 build upon the findings of the ERC-AdG Scale-FreeBack (emob-), resulting in an e-mobility simulation tool driven by digital twin technology. eMob-Twin serves a wide range of purposes including forecasting, analysis, and unlocking EV flexibility, catering to the needs of companies, stakeholders, and electricity markets. Initially designed for the Grenoble metropolitan area, a new version currently under development, eMob-TwinV2, will have the capability to encompass any other metropolitan city in France, incorporating auto-calibration functionalities. Primarily focused on electric vehicle (EV) mobility and their state of charge, it also integrates multi-power charging stations. In the context of the PEPR-FORBAC initiative, we aim to tackle two primary challenges. Firstly, we seek to optimize the placement of charging stations (PC location) to ensure efficient coverage. Secondly, we aim to optimize power delivery density per unit area, utilizing the steady-state solution of the dynamic electromobility model while adhering to energy equilibria constraints (ensuring EV charging demand matches the charging station supply infrastructure). Results will be integrated as a toolbox in the eMob-Twin V2 software.

Principales activités:

Work program.
The work program includes several key areas of development, focusing on model extensions, large-scale optimization challenges, and software implementation:

  • Expanding the existing model referenced in [1, 2] to incorporate additional nodes representing Charge Stations with actual capacity, driveruser price models, and their integration with the grid,
  • Following ideas in [2], devising highly efficient optimization algorithms (including learning and IA strategies) for charge station placement and power delivery density per unit area within the expanded model framework. These solutions should be scalable to cover the entire graph model,
  • Integrating the developed algorithms (both the model extension and optimization algorithms) into eMobTwin V2, and conducting comparative analyses of optimization outcomes with those provided by policymakers and urban planners (SDRIVE).
The integration of software components will be undertaken with the assistance of our local team of Research Engineers.

References

  • Rodriguez-Vega, M., Canudasde Wit, C., Nunzio, G.D., and Othman, B A graphbased mobility model for electric vehicles in urban traffic networks: Application to the Grenoble metropolitan area. In 2023 European Control Conference (ECC), Bucarest, Ru.
  • Mourgues, R., and Canudas-DeWit, C., Rodriguez-Vega, M., Optimal location of evs public charging stations based on a macroscopic urban electromobility In nd IEEE Conference on Decision and Control (CDC),

Compétences:

Request Background. Optimization, Applied mathematics, physical modeling, IA

Avantages:

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Rémunération:

  • 2788 euros/month gross salary

Informations générales:

-
Thème/Domaine: Optimisation, apprentissage et méthodes statistiques
Calcul Scientifique (BAP E)

-
Ville: Montbonnot

-
Centre Inria: Centre Inria de l'Université Grenoble Alpes
-
Date de prise de fonction souhaitée:
- **Durée de co

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