Statistical physics of networks and material circuits in energy transition scenarios
|Contact: Bercegol Herve, , firstname.lastname@example.org, +33 1 69 08 74 37|
In the context of the ongoing energy transition, the aim is to develop statistical physics models applied to the understanding and forecasting of the evolution of energy networks.
|Possibility of continuation in PhD: Oui|
|Deadline for application:20/04/2022 |
|Full description: |
The energy transition is underway, involving or implying major changes in energy networks as well as in the use of materials, at the local and global scales. Statistical physics has often been used to study the stability of electrical networks, and even the coupling between networks. We propose to use it here to study the evolution of networks and associated infrastructures, from the geometrical point of view and from the point of view of the spatial distribution of materials.
Can we define the characteristics of the physical network - or of the different networks - that make the transition possible?
Can we define an optimal distribution of energy storage, and according to what criteria?
What is the interaction between stocks and flows of materials: flows needed to maintain the network and the infrastructure, stocks needed for a reliable energy storage making the system robust, and sufficiently well distributed to allow a relevant and efficient distribution of materials?
Based on several decades of study of the key role played by energy consumption and material transformation in the economy, and on a thorough analysis of the existing system, in terms of empirical logistical knowledge as well as statistical physics, this thesis will establish a model of the coupled energy and material networks: one of the objectives of the model will be to evaluate the different possible, probable and/or desirable evolutions, in terms of efficiency (energy and material), stability and robustness.
This thesis, at the interface between physics and economics, will be followed by an inter-institute scientific committee within CEA (DRF/Iramis, DRF/Irfu and DES/I-Tésé).
|Technics/methods used during the internship: |
Mathematical modelling Numerical programming Statistical physics
|Tutor of the internship |