Transmission system adequacy evaluation considering wind power
Bibliographic record
Abstract
There has been a rapid growth of renewable power applications in electrical power generating systems due to concerns over the environment and depleting sources of conventional power generation. Implementation of policies such as the renewable portfolio standard, have mandated many regions around the globe to significantly increase renewable power penetration in electrical power systems. Wind power is the most important renewable energy source in meeting these targets, and its application is increasing rapidly in small power systems and large grid connected systems. Power generated by wind depends on the availability of the wind, which changes intermittently and varies randomly from zero to the rated capacity of the wind farm. It is difficult to assess the capacity credit of a wind farm and the appropriate capacity requirement of transmission facility to transfer wind power to the system load. There is a need to develop realistic reliability/cost evaluation techniques considering wind power in a power system including the transmission system. This paper presents an analytical method to evaluate transmission system adequacy for wind power. The paper illustrates results using an example wind farm. The presented methods and discussions should be useful to power system planners and policy makers.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".