Adequacy assessment of generating systems containing wind power considering wind speed correlation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wind power is an important renewable energy resource. Electrical power generation from wind energy behaves quite differently from that of conventional sources, and maintaining a reliable power supply is an important issue in power systems containing wind energy. In these systems, the wind speeds at different wind sites are correlated to some degree if the distances between the sites are not very large. Genetic algorithm methods are applied here to adjust autoregressive moving-average time series models in order to simulate correlated hourly wind speeds with specified wind speed cross-correlation coefficients of two wind sites. Multi-state wind energy conversion system models are used to incorporate the correlated wind farms in reliability studies of generating systems. A method to generate random numbers with specified correlation coefficients for application in a state-sampling Monte Carlo simulation technique is introduced. It is shown that the proposed method can be used in the adequacy assessment of a generating system incorporating partially dependent wind farms.
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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 | 0.001 |
| 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 it