Thermal mass and energy recovery utilization for peak load reduction
Bibliographic record
Abstract
Highly energy performing buildings need cost effective solutions which can deliver specified indoor climate and energy performance targets. In this study temperature variation of indoor climate category II according to EN 15251 standard is applied with the aim to allow free floating temperatures in this range to activate internal thermal mass of walls. Main hypotheses are that interior thermal mass of enough thick concrete layers can enable utilization of solar and internal gains resulting in significantly reduced peak loads for both heating and cooling, and reduced overall energy need. In this study, dynamic energy simulations are conducted to identify optimal solutions for a planned experimental building. Impact of energy recovery system on annual heating/cooling need and interior thermal mass on cooling design load are studied. Proposed energy recovery system consists of a piping layer installed into internal layer of a wall or floor structure and coupled with storage tank via piping and circulation pump. This system operates only when specified temperature differences exist that is expected to store excess room heat or cool within accepted indoor temperature range and to distribute it into other building zones. Modelling is performed in dynamic whole year simulation environment IDA-ICE, where a simplified two-zone model of a single-family house along with energy recovery system are modelled. Zones envelope and interior structures are modelled with finite difference wall/floor model accounting for thermal capacitances of structures material layers and exposure to solar radiation passing through detailed window model. Model of a piping layer connected to finite difference wall or floor structure computes heat transfer using logarithmic temperature difference. Rest of the energy utilization system is modelled using IDA-ICE standard model library components. Results reveal that interior thermal mass has significant impact on peak loads and energy need reductions. Modelled energy recovery system is capable of significantly reducing heating need as long as high system flow is maintained.
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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".