Empirical assessment of short‐term variability from utility‐scale solar PV plants
Bibliographic record
Abstract
ABSTRACT Variability of solar power is a key driver in increasing the cost of integrating solar power into the electric grid because additional system resources are required to maintain the grid's reliability. In this study, we characterize the variability in power output of six photovoltaic plants in the USA and Canada with a total installed capacity of 195 MW (AC); it is based on minute‐averaged data from each plant and the output from 390 inverters. We use a simple metric, “daily aggregate ramp rate” to quantify, categorize, and compare daily variability across these multiple sites. With this metric, the effect of geographic dispersion is observed, while controlling for climatic differences across the plants. Additionally, we characterized variability due to geographical dispersion by simulating a step by step increase of the plant size at the same location. We observed maximum ramp rates for 5, 21, 48, and 80 MWAC plants, respectively, as 0.7, 0.58, 0.53, and 0.43 times the plant's capacity. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.006 |
| 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 | 0.001 | 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 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".