Operating thermal source networks – How supply temperature and ground exchange shape performance

Thermal source networks (TSNs) operate at low temperatures and supply heating and cooling simultaneously. Their performance depends strongly on supply-temperature scheduling, and the thermal behaviour of often uninsulated, shallow-buried pipes. This work develops two transferable tools for TSN analysis – a minimum pipe–ground modelling standard and a unified KPI taxonomy – and demonstrates them on a representative cooling-dominant case. A MATLAB/Simscape model of a representative industrial TSN – based on the incampus site and comprising five buildings with reversible heat pumps, an energy hub, and nine distribution segments – compares four supply temperature control strategies (STCS). Balanced energy, heat/cold gains/losses, network heating/cooling ratios (NHR/NCR), and seasonal performance factors are evaluated within the taxonomy. To quantify modelling uncertainty, quasi-steady resistance(R)-only and first-order resistance-capacitance (RC) pipe–ground models are compared to a transient multiphysics reference and commissioning data. The RC model matches the reference’s cumulative losses within −4%, whereas the R-only model deviates by +26%. Against the commissioning data, the RC model also reproduces thermal power more accurately. The STCS comparison reveals clear trade-offs. The free-floating scenario maximises balanced energy and yields the best NHR (108%) and NCR (174%). The ground-guided scenario limits pipe–ground heat exchange by tracking the undisturbed ground temperature while maintaining high network ratios. The demand-guided scenario prioritises building efficiency, yielding the highest seasonal performance factor (7.78), albeit with lower network ratios. An illustrative price-scenario analysis indicates the favourable STCS is price-contingent. The transferable workflow, models, and performance indicators provide a transparent basis for TSN operational analysis and control prototyping.