Geo.KW - Coupling hydrothermal and infrastructure modeling at urban scale for an efficient use of shallow geothermal energy

To reduce anthropogenic climate change, the energy demand from all energy sectors has to be met by renewable energies, wherever possible.
Shallow geothermal energy usage, powered by green electricity, provides heating/cooling at a high level of efficiency, which is difficult to achieve with renewable energy alone.
We have created a coupling approach, which combines hydrothermal and infrastructure modeling at an urban scale to efficiently position shallow geothermal systems between existing power plants and conflicting groundwater usage, optimised by economical and ecological contraints.
We are using Pflotran, a finite volume Darcy-Richards model for our hydrothermal model.
The implementation of the energy infrastructure is done with urbs, a linear optimisation model for distributed energy systems.
We utilize preCICE, a coupling library for multi-physics simulations, for fully parallel peer-to-peer data exchange between these modeling domains.
Iterative optimization is meant to ensure the convergence of the fully coupled model.