Inertial response from wind power plants during a frequency disturbance on the Hydro‐Quebec system – event analysis and validation
Bibliographic record
Abstract
To better assess the contribution of wind power plants (WPPs) during disturbances, Hydro‐Québec TransÉnergie (HQT), the main transmission system operator in the Quebec Interconnection, uses on‐line monitoring to record data at the point of common coupling of each WPP. This data is used to analyse their performance during voltage and frequency disturbances. Until recently, very few WPPs were able to provide an inertial response (IR) for under‐frequency events. On 28 December 2015, a generation loss of 1700 MW caused a frequency nadir of 59.08 Hz on the system, to which most WPPs required to provide IR contributed significantly. The analysis of the event showed that the behaviour of the WPPs had a significant effect on the recovery of the system frequency. This study presents the performance analysis of WPPs during this under‐frequency event. The analysis is based on data collected from 25 large‐scale WPPs in operation and equipped with the IR feature as required by HQT. Field measurements and simulation results are used to emphasise the effect of the active power reduction during the recovery phase. Impacts of the IR from the WPPs as used on the Hydro‐Quebec system are discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".