A Regulation-Caused Bottleneck for Regulating Power Utilization of Balancing Offshore Wind Power in Hourly- and Quarter-Hourly- Based Power Systems
Bibliographic record
Abstract
In Denmark, the operation experience from the Horns Rev I offshore windfarm (160 MW) located in the North Sea showed that power output of the windfarm was characterised by intense, rapid and repeating fluctuations due to unsteady wind conditions. In certain wind conditions, the power output from the offshore windfarm changes between zero and rated power levels in faster than a quarter of an hour, introducing power fluctuations of a repeating character to the Danish transmission grid. Such intense power fluctuations may last for several hours, introducing a power-balance challenge to the Danish transmission system. Many transmission systems, including the Nordic system which Denmark is part of, are hourly- and quarter-hourly- based regarding the power generation plans, power balance and agreed power transmission between the countries. Applying the Nordel1 cooperation regulations and a simplified grid equivalent of a hydro-power-based transmission system with the main generation and consumption figures of Norway, this paper shows that such hourly- and quarter-hourly- system operation regulations may introduce a bottleneck for efficient utilization of available regulating power with increasing grid-integration of large offshore windfarms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".