Transformer Load Distribution Optimization using Dynamic Power Dispatch in Commercial Buildings
Bibliographic record
Abstract
On-Site measurements confirmed that dry-type distribution transformers (DDTs) supplying the electrical distribution grid (EDG) in commercial buildings (CB) are typically underloaded, therefore working at lower-than-expected efficiency values.Investigative research revealed a new active energy conservation measure (AECM) called Dynamic Power Dispatch (DPD). The DPD principle is based on the Unit Commitment (UC) algorithm with Objective Function of minimizing power losses in EDGs.This paper describes an applied research project that verifies the DPD concept leading to energy and power savings within EDG of CBs.Through calculations, simulations, and practical testing on a 1:1 physical model, the DPD methodology was verified.According to energy savings estimates for Canada, the DPD concept would have an estimated 83 GWh per year of energy savings in CBs.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".