Optimizing design of household scale hybrid solar photovoltaic + combined heat and power systems for Ontario
Bibliographic record
Abstract
This paper investigates the feasibility of implementing a hybrid solar photovoltaic (PV) + combined heat and power (CHP) and battery bank system for a residential application to generate reliable base load power to the grid in Ontario. Deploying PV on a large-scale has a penetration level threshold due to the inherent power supply intermittency associated with the solar resource. By creating a hybrid PV+CHP system there is potential of increasing the PV penetration level. One year of one second resolution pyranometer data is analyzed for Kingston Ontario to determine the total amount of PV energy generation potential, the rate of change of PV power generation due to intermittent cloud cover, and the daily CHP run time required to supply reliable base load power to the grid using this hybrid system. This analysis found that the vast majority of solar energy fluctuations are small in magnitude and the worst case energy fluctuation can be accommodated by relatively inexpensive and simple storage with conventional lead-acid batteries. For systems where the PV power rating is identical to the CHP unit, the CHP unit must run for more than twenty hours a day for the system to meet the base load requirement during the winter months. This provides a fortunate supply of heat, which can be used for the needed home heating. This paper provides analysis for a preliminary base line system.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".