Development and validation of a system dynamics model for geothermal energy networks

As cities and utility companies seek to decarbonize building heating and cooling systems to meet regulatory standards and emissions targets, geothermal energy networks (GENs) have emerged as a viable pathway for delivering low-emission thermal services at scale. However, GENs exhibit complex interactions between subsurface resources, engineered surface systems, and techno-economic constraints that are poorly captured by traditional simulation platforms. This paper presents a novel base model for GENs built using a system dynamics (SD) framework that enables the simulation of transient, nonlinear behavior across thermal, hydraulic, economic, and maintenance subsystems. The model represents GEN variants that include both centralized and distributed heat pumps, aquifer or borehole thermal storage, and dynamic building thermal loads. Core sub-models integrate heat exchanger effectiveness, thermal losses, ground temperature response, and pump performance with feedback mechanisms governing equipment degradation, maintenance intervals, and economic viability. The GEN model is validated against GLHEPro for vertical ground heat exchangers and demonstrates a mean squared error of 2.27 °C for the outlet temperature with an R² of 0.92. Comparative simulations between simplified aquifer and borehole-based GENs indicate significant differences in energy intensity, with aquifer systems consuming more electricity over 20 years due to increased pumping demands, despite higher heat pump efficiency. The SD framework captures critical behavior – such as thermal degradation in boreholes, fouling-induced efficiency losses, and maintenance-induced recovery – that static or high-fidelity engineering models often neglect. Importantly, the model operates at hourly timesteps across multi-decade horizons with minimal computational burden, allowing for extensive sensitivity analyses and integration of social, economic, and policy scenarios. Future extensions include market penetration modeling, emissions accounting, and resilience analyses. By bridging engineering and socio-economic dynamics, this SD-based GEN model offers a powerful tool for designing and regulating next-generation district energy infrastructure.