2003: Energy performance of daylight-linked automatic lighting control systems in large atrium spaces: report on two field-monitored case studies
Bibliographic record
Abstract
This paper presents the field-measured energy performance of two common types of daylight-linked lighting control systems, continuous dimming and automatic on/off installed in two existing large atrium spaces located in Canada. The daylighting performance was evaluated based on the daylight contribution to the indoor illuminance and the amount of electrical lighting displaced by daylighting via the daylight-linked lighting control systems. Measured daylighting contribution to the space indicates that significant lighting energy savings can be achieved in atrium spaces if the daylight-linked lighting control system is appropriately selected, installed and commissioned throughout its existence. Results extrapolated from measurements collected during summer and winter indicate that as installed, the continuous dimming lighting control system provides 46% annual savings in electrical lighting consumption, while the automatic on/off saves between 11-17% in lighting energy. These savings account for 68% of the lighting energy consumed during main occupancy for the continuous dimming system, and 31.5% for the automatic on/off. Operation irregularities such as a reduced dimming linearity and an incorrect adjustment of the phases of the dimming control system, as well as the inadequate location of the photocell controlling the automatic on/off lighting system, the improper maintenance of the skylight during winter and the oversizing of the lighting system reduced the energy efficiency of the lighting control systems by 30-65%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".