Urban-Scale Borehole Heat Exchanger Network Optimisation in Groningen: GIS–Python workflow with iterative demand assignment, g-functions and depth sizing

Abstract

Borehole Heat Exchangers (BHEs) are a promising solution for decarbonising space heating and cooling in urban environments. However, large-scale deployment requires careful planning to account for limited drilling space, thermal interaction between neighbouring systems, and the need to allocate demand in a spatially consistent way. This thesis presents an end-to-end GIS–Python workflow to support urban-scale BHE planning for the city of Groningen. The pipeline integrates building-level heating and cooling demand with cadastral parcels and subsurface thermal property descriptors. It combines geometric feasibility rules for borehole placement with a scalable interaction indicator derived from borehole layouts, and a thermal sizing model that determines the minimum borehole depth required to meet assigned loads under temperature constraints. Akey contribution of the methodology is an iterative coupling between demand allocation and depth sizing. Building demand is assigned to nearby boreholes under practical distance and capacity constraints, after which borehole depths are resized to satisfy the updated assigned loads. Repeating this loop improves internal consistency between the spatial allocation of demand and the resulting borehole designs, and allows constraint-driven patterns to emerge in a traceable way. The workflow produces network-wide indicators such as depth distributions, capacity utilisation and assignment reach, as well as GIS-ready spatial outputs at borehole, parcel and block level. Overall, the proposed approach provides a reproducible and transparent framework for screening and interpreting urban-scale geothermal feasibility, and can be adapted to other cities with comparable datasets.

Outgoing