Characterization and modelling of the geothermal behaviour of the ground supplying a 5th generation (5G) heating and cooling district networks PhD Jeanne Sauvenier

Characterization and modelling of the geothermal behaviour of the ground supplying a 5th generation (5G) heating and cooling district networks.

5th generation (5G) heating and cooling district networks allow for the exchange of heating and cooling demands among interconnected buildings. Connecting this network to a geothermal system (open- or closed-loop systems) makes it possible to use the ground as a thermal reservoir and to stabilize the temperature of the network. However, uncertainty regarding the geothermal potential of the ground remains a major obstacle to the development of this technology. To better assess this potential, this project aims to refine predictive models of the temperature field around geothermal systems under complex thermal loads, using two research approaches.

(i) Innovative geophysical techniques will be deployed at two scales. At the network scale, geological heterogeneities will be detected through electrical tomography to identify areas of priority interest. At the local scale, electrical tomography will be combined with thermal stimulation of the subsoil to track the evolution of heat plumes and thus determine local geothermal parameters.

(ii) Various modeling methods will be evaluated to predict temperature field changes in the subsurface. This modeling will also be conducted on two scales: locally, around active geothermal systems, and globally, at the network scale.

Taking an interdisciplinary approach (geothermal energy, geophysical characterization, heat networks, and building energy performance), this methodology will be applied to studying a 5G heat network at the Polytech district (ULiège Campus - Sart-Tilman).

Thus, existing geothermal infrastructure (four geothermal probes, a pumping well, and two geothermal doublets), preliminary knowledge of the local geology, and the energy needs of the buildings (monitored since 2021) will be integrated into the theoretical design of the network, combining the findings from this project.