Thermal performance of a solar hot water system : model versus measurement
Bibliographic record
Abstract
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.
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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".