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

2025· article· en· W4413143648 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeothermics · 2025
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of Calgary
FundersNational Renewable Energy Laboratory
KeywordsGeothermal gradientGeothermal energyModel validationSystem dynamicsGeologyEnvironmental scienceSystems engineeringEngineeringComputer scienceGeophysicsData science

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.184
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it