Thermal performance of a solar hot water system : model versus measurement
Notice bibliographique
Résumé
A commercially available solar domestic hot water heating system installed in a private residence in Vancouver, B.C. has operated continously and reliably since it was commissioned in April 1981. The system employs a water-based, double tank, drainback design; components include a flat plate collector array, solar storage tank with immersed coil heat exchanger, circulation pump, differential controller, and auxiliary hot water tank. Project monitoring of the system using an automatic data acquisition and logging system commenced in June 1981 and continued to December 1982. Storage tank, water supply line and ambient air temperatures, together with solar radiation, hot water consumption, solar / total heat delivered, and auxiliary fuel consumption were integrated or averaged hourly; pump operating hours were recorded daily. The completeness, consistency, and quality of the data collected over the 19 month monitoring period has been established. The system's thermal performance and operating characteristics are evaluated and analyzed. Results incorporate information on: the hot water heating load and fraction supplied by solar energy, the operating efficiency of the system and its components, the storage tank and water supply line temperatures, and the amount of conventional energy saved.. A separate account is given of the users' hot water consumption patterns. Over the monitoring period the system utilized 38.0% of the solar radiation incident on the collector array. The resulting solar energy contribution to the hot water heating load was 47.5%. However, there was large diurnal, day-to-day, and seasonal variability in the system's thermal performance. This was a direct result of the highly variable combination of load and meteorological conditions imposed on the system, together with its limited thermal storage capability. A problem was encountered in evaluating the system's performance during the late fall and early winter months due to the existence of standby heat gain. The latter resulted from the storage tank temperature decreasing below that of the surrounding basement air during periods of low and zero solar energy input. Simulation of the system was performed using a modified version of the WATSUN-3 Domestic Hot Water (DHWA) model (Chandrashekar and Wylie, 1981a). This model assumes that the storage tank is fully mixed and isothermal at all times, and that the system variables remain constant over each one hour time step. Modifications made to the model include changes to the input data specifications, collector control strategy, immersed coil exchanger and standby heat loss calculations. Input data for the model were derived from three sources: measured hourly data for the load and meteorological variables, manufacturer's specifications for the system component parameters, and externally performed test results for the collector efficiency parameters. Model predictions are compared against actual system measurements for both a two month and a year long simulation period. Although the model was able to consistently track thermal conditions in the storage tank, it exhibited a seasonally dependent negative bias. This limited its ability to predict the system's long term thermal performance; the estimated annual solar fraction deviated by -15.8 percent. Identification of the cause(s) of the model bias was hindered by lack of sufficient monitoring data. A sensitivity analysis, undertaken to assess user-effect errors, revealed that several of the input variables associated with the collector component model were potential sources of inaccuracy. Thus further testing and evaluation of the simulation model, using more rigorous and detailed measurement data, is required before the model can be used with confidence.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».