Hybrid Solar Geothermal Heat Pump System Model Demonstration Study
Bibliographic record
Abstract
In this paper, the development and demonstration of a hybrid solar geothermal heat pump polygeneration system is presented. The poly-generation system has been designed, modeled, and simulated in TRNSYS software environment. Its performance was assessed followed by installation and demonstration at a demo site in Cheongju, Korea. The space heating and cooling load of the building is 13.8 kW in heating mode at an ambient temperature of −10.3°C and 10.6 kW in cooling mode at an ambient temperature of 32.3°C. The simulation data were compared with the field demo data using ISO 13256. The results showed that the model data compare well with the demo data both in heating and cooling modes of operation. At a source temperature of 16.7°C, the heat pump lab performance data-based COPc shows 9.9, while demonstration COPc shows 10.3, thus, representing 4.3% relative error. The heat pump source temperature decreased by 4.0°C from 20.9°C to 16.9°C due to ground heat exchanger coupling and resulted in a COPc increase by 13.3% from 8.5 to 9.8. When compared at the design conditions (outside temperature of 32.3°C), the TRSNYS model overestimated the demonstration site data by 12%, 9.3 vs. 8.1 kW with power consumption of 3.1 vs. 2.2 kW. The hybrid polygeneration system power consumption decreased by 1.2 kW when ambient temperature decreased from 35°C to 25°C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".