Application of PCM to shift and shave peak demand: Parametric studies
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».