Thermal Performance of a Geothermal Source High-Temperature Heat Pump for District Heating – Comparison of Single-Stage and Cascade Vapor Compression Cycles
Bibliographic record
Abstract
Abstract Reducing greenhouse gas emissions is of utmost importance in the race to keep the global average temperature increase to within 1.5°C of pre-industrial levels to avoid catastrophic consequences of climate change. In cold climates, a large portion of carbon dioxide emissions come from the heating requirements of buildings, primarily space heating and hot water heating. Large institutional and commercial buildings use considerable amounts of energy to provide space heating and hot water, most of which comes from large-scale district heating systems powered by fossil fuels. There is therefore potential for emission reduction in institutional and commercial buildings using clean and renewable energy. This study investigates the use of high-temperature heat pumps in a high-temperature district heating system for a University Campus. The considered heat pump system meets 51 MWth of heating demand. The heat pump is coupled to a geothermal borehole 2 km in depth whose performance is modeled using CMG software for thermal reservoir modeling to improve its performance. The performance of the heat pump system using R134a is compared with that of environmentally friendly refrigerants, including R1233zd(E), R1366mzz(Z), R1234ze(Z), Butene, ammonia, R1224yd(Z), and RE245CB2. Results show that the cascade system yields higher average COPs regardless of the refrigerant due to lower compressor energy inputs. Results further show that using refrigerant R1233zd(E) in both system stages produces the best performance, with an average COP of approximately 3.0. Furthermore, for the building energy loads considered, high flow rates between 500 m3/h to 6000 m3/h are needed to meet the entire heating demand depending on the temperature difference between the inlet and outlet temperatures of the geothermal heat transfer fluid.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".