Optimal Sizing and Operation of Electric Thermal Storage Systems for the Multi-zone Residential Apartment Building
Why this work is in the frame
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Bibliographic record
Abstract
The escalating energy demand and peak consumption periods during winter pose strenuous challenges. The rapid growth of electricity demand intensifies the risk of energy shortages. Strategic measures are imperative to mitigate the impact of winter peak periods on the grid and the increasing electrical load from conventional heating systems. To address such a challenge, this paper presents a methodology for determining the optimal size and operation of electric thermal storage (ETS) in multi-zone residential apartment buildings by forming an optimization problem. The economic implications of employing ETS with time-of-use (TOU) price signals and its impact on load shifting are explored. A synthetic energy consumption dataset of a residential building in Quebec, Canada, is utilized to evaluate the proposed method. Simulation results demonstrate that the judicious use of ETS, especially with dynamic electricity rates, enhances consumer economic savings by 66.54% and satisfies the energy demand.
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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 | 0.000 | 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 it