Directional Solar Variability Analysis
Bibliographic record
Abstract
The irradiance at ground level mostly fluctuates due to cloud coverage. As clouds are moving toward a certain direction, the cardinal orientation of photovoltaic arrays affects the variability of the output power, and thus the impact on the electric power grid. This paper presents a new methodology with a circular layout for irradiance monitoring units to assess the solar variability in different directions of any site based on cloud speed-direction trend and directional variability reduction. The proposed methodology is used to assess the directional variability for a site at Varennes, QC, Canada using 1 year of measured data. The cloud speed direction is studied in order to observe any trend from a month-to-month and from an hour-to-hour. Overall the cloud direction has a trend of West to East direction, especially during the winter months. The variability reduction for each axis is estimated using the variability index (VI). The largest VI reduction is observed close to the cloud direction axis.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".