Application of PCM to shift and shave peak demand: Parametric studies
Bibliographic record
Abstract
Space conditioning is a main contributor to energy usage in buildings. In Quebec, electric baseboard heaters are the predominant household space-heating systems, in the other words, electrical energy is the main source of energy used for space heating. Thus in such a cold climate like Quebec, residential peak heating demand is a significant contributor to high and critical electricity grid peak periods. Reducing peak heating demand by shifting a portion of peak heating demand to off-peak period is thus of high interest. On the supply side, this strategy requires less generated power, and on the demand side it helps downsize heating systems. One possible approach to shifting peak heating demand to off-peak time is to store thermal energy during off-peak periods and release the stored energy during peak periods. To adopt this approach, set-point temperature of heating systems can be lowered during the peak period, while a release of stored energy maintains the indoor temperature within the desired comfort zone. This capability could be implemented using the concept of latent heat, offered by phase-change-material (PCM)–impregnated building wallboard, such as PCM-gypsum wallboard. In this thesis, a PCM module within TRNSYS software is first validated with experimental data, available in literature, for a simple case of one cubicle. The code is then applied to a typical one-story residential building, also modeled in TRNSYS. Later, several parametric studies are carried out to investigate the influence of PCM’s thermal properties and convective heat transfer coefficient on the rate of PCM’s thermal discharge and its resulting improvement in indoor air condition. The simulation results reveal that it is possible to maintain a trade-off between shifting the peak heating demand and preserving thermal comfort by applying PCMs with proper characteristics. It was observed that improving thermal conductivity of PCM has a negligible impact on heat discharge during peak time. Simulations also show that the PCM melting temperature range should be chosen closest to the assigned set-point temperature. It has been shown that increasing the thickness of the PCM layer more than a certain value, 0.013 m, has no effect on thermal storage or, therefore, on PCM thermal discharge. Investigation of interior convective heat transfer on PCM discharge reveals that for a specific climate and PCM wallboard, there is a threshold for effective performance of PCM. For a building located in Montreal, it was shown that with a typical PCM-gypsum wallboard, the interior heat transfer coefficient has to be at least 6.6 W/m2K to sustain the desired thermal comfort. Finally, thermal behavior of the building integrated with PCM wallboards was assessed in three different climates and by applying two different PCM-gypsum wallboards. It was found that PCM wallboard selection and set-point temperature control strategy must be considered according to the outdoor weather conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".