Performance Evaluation of a Combined Heat and Power Generation System with Borehole Thermal Energy Storage: A Feasibility Study of a Combined Heat Pump and Organic Rankine Cycle System
Bibliographic record
Abstract
The current research is focused on the introduction of a heat pump (HP)-assisted organic Rankine cycle (ORC), which runs on the heat extracted from a high-temperature borehole thermal energy storage (BTES). By varying different source temperatures from 40 °C to 60 °C, the HP cycle works to upgrade the heat to run the ORC. Different combinations of environmentally friendly fluids are studied in comparison to match the top and bottom cycles and to make the overall system a combined heat and power (CHP) system. A power sufficiency condition is defined to compare and identify the best working fluid combination for the HP cycle and ORC. Based on the analysis, ammonia for the HP and R1234zee for the ORC emerged to be a suitable combination among all the studied combinations. As an example, for a BTES heat source of 237 kW at the source temperature of 60 °C, the BTES–HP–ORC–district heating system with the ammonia–R1234zee pair has resulted in the HP compressor work input of 21.9 kW with the coefficient of performance (COP) of 10.9 for the HP cycle and the ORC net work output and district heating supply of 10.4 kW and 209 kW, respectively, with the thermal efficiency (η) of 4.3% for the ORC at the evaporation temperature of 65 °C. A study in terms of the greenhouse gas (GHG) emissions reveals the feasibility of the system depending on the regional GHG intensity and emission factor of electricity and natural gas.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".