Reliability Evaluation Considering Wind and Hydro Power Coordination
Bibliographic record
Abstract
Wind energy application in electric power systems continues to increase globally. The contribution of wind farms to the overall system reliability is limited by the uncertainty in power output from these highly variable energy sources. The ability of a power system to absorb available wind energy and maintain the system reliability and stability is reduced as the wind penetration in the system is increased. It therefore becomes important to coordinate the operation of wind power with fast responding conventional generating units. Hydro facilities with energy storage capability can alleviate the impact of wind power fluctuations and also contribute to system adequacy. A methodology for an energy limited hydro plant and wind farm coordination is developed using a Monte Carlo simulation technique considering the chronological variation in the wind, water and the energy demand. The IEEE four-state model is incorporated in the developed technique to recognize the intermittent operation of hydro units. The proposed approach is applied to the IEEE-RTS, and quantitative assessment of reliability benefits from effective utilization of wind and water resources are conducted through a range of studies. The effects of major system parameters on the system adequacy are also investigated.
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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 | 0.006 |
| 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) | 0.001 | 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 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".