Improving the Efficiency of Stand-Alone Solar PV Power Plants
Bibliographic record
Abstract
As a source of alternative energy, solar energy has apparent advantages, including a renewable, inexhaustible, and environmentally friendly resource. However, it has not become widely spread in the Russian Federation. Among the disadvantages of using solar energy are high equipment cost, low efficiency of photovoltaic solar cells, the generated electrical energy instability. The spatio-temporal variability of solar access causes electrical energy instability. It is possible to increase solar photovoltaic plant efficiency by using a tracking system to change the plant sun's spatial orientation. The paper offers mathematical and simulation models of a solar photovoltaic plant with a solar tracking system that allows the plant to be automatically oriented to the sun by matching the production mode and the solar access level. The use of the azimuth plant control system on the sun will increase the power production of the solar PV plant by an average of 28%. The same value will increase by 40% when using the full plant control system.
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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 | 0.000 |
| 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 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".