Developing and testing a generic micro-combined heat and power model for simulations of dwellings and highly distributed power systems
Bibliographic record
Abstract
This paper elaborates an approach to the modelling of domestic micro-combined heat and power (μ-CHP) using a building simulation tool that can provide a detailed picture of the environmental performance of both the μ-CHP heating system and the dwelling it serves. The approach can also provide useful data for the modelling of highly distributed power systems (HDPS). At the commencement of the work described in this paper no μ-CHP device model that was compatible with a building simulation tool was available. The development of such a model is described along with its calibration and verification. The simulation tool with the device model was then applied to the analysis of a dwelling with a Stirling engine-based heating system. Different levels of thermal insulation and occupancy types were modelled. The energy and environmental performance of the μ-CHP device was quantified for each case; additionally, the potential for its participation in the control and operation of an HDPS was assessed. Analysis of the simulation results indicated that the parasitic losses associated with the μ-CHP system balance of plant reduced the overall heating system efficiency by up to 40 per cent. Performance deteriorated with increasing levels of insulation in the dwelling, resulting in reduced thermal efficiency and increased cycling, though overall fuel use was reduced. The analysis also indicated that the device was generally available to participate in HDPS control for greater than 90 per cent of the simulation time. The potential length of the participation time ranged from 1 to 800+min and depended upon the state of the μ-CHP system thermal buffer and prevailing heat loads. Probabilities for different participation times and modes were calculated.
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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".