Weighted Dynamic Aggregation Modeling of Induction Machine-Based Wind Farms
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Bibliographic record
Abstract
This paper presents Weighted Dynamic aggregation (WD agg) method to obtain an equivalent Wind Turbine Generator (WTG) for an induction machine-based wind farm using its dynamic model. The suggested approach obtains the equivalent d-q model of the induction generators considering the contribution of each unit in the model. The challenges in the aggregation of a large-scale wind farm are the variation of wind speeds at different zones and differences in the WTGs parameters. Compared with the existing methods such as Full aggregation (Full agg), Zone aggregation (Zone agg), and Semi aggregation (Semi agg), the suggested WD agg method provides an accurate single unit equivalent model for a large-scale wind farm while taking into account various wind speed zones and unequal WTG parameters. The proposed method is evaluated through time-domain simulation of a 4-WTG and a large-scale 20-WTG Doubly-Fed Induction Generator (DFIG) wind farms and their aggregated models. These simulations cover combinations of different wind speeds and WTGs parameters. Also, a 4-WTGs fixed-speed wind farm is studied to show the generality of the proposed method. Comparing WD model with the detailed response of the wind farm verifies the accuracy of the method in both steady-state and transient behaviors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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