Evaluating the Impact of Time-of-Use Billing on Energy Costs in a University Building in Newfoundland, Canada
Bibliographic record
Abstract
Globally, buildings contribute to about 30% of total energy demand, with over half of this consumption in Canada attributed to space heating and cooling. This presents an opportunity for substantial energy and cost savings. Many buildings are transitioning to electric heating for efficiency and cost-effectiveness, but different tariff structures can result in unexpected cost increases, necessitating adjustments to the building's regular operational patterns to mitigate expenses. This study employs a building energy model developed with the OpenStudio application to conduct a comparative analysis, focusing on the impact of various tariff structures using the MUN CSF building as the case study. It investigates the impact of transitioning from a flat-rate tariff to a time-of-use tariff on energy costs, even with the adoption of energy-efficient electric resistive heating compared to the current oil-fired hot water boiler. The findings indicate that the retrofit, which proves cost-effective under a flat-rate tariff, might not yield financial savings and could potentially increase energy costs under a time-of-use tariff. The simulation results show an energy cost of CA$1,029,089 under the flat-rate tariff, derived from historical data, and CA$1,980,110 under the time-of-use tariff, based on current tariffs in Newfoundland and Ontario. This suggests that energy costs under the time-of-use tariff can nearly double compared to the flat-rate tariff, with the same amount of energy consumed and a similar usage pattern.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".