Voltage flicker assessment in distribution feeders with large wind farms
Bibliographic record
Abstract
In recent years, Doubly Fed Induction Generator (DFIG) wind turbines connected to rural distribution feeders represents an emerging trend that has experienced growth.Higher penetration levels of embedded wind generation has interesting benefits (i.e.peak-shaving, congestion alleviation, reduction of losses, etc.) but raises important issues concerning the quality of power delivered to utility consumers.This thesis investigates the technical limitations involved with integrating large DFIG based wind farms into existing distribution feeders with regard to voltage flicker.This dissertation includes an overview of firstly, the applicable Electromagnetic Compatibility (EMC) standards related to the measurement and assessment of flicker emissions produced by distribution-connected wind farms.Secondly, aerodynamic, turbine and feeder characteristics which influence voltage flicker.Thirdly, the level of modeling required to conduct a pre-connection flicker study.Based on these three aspects, flicker emissions produced by a DFIG are quantified and a rule of thumb and a set of guidelines are presented for the acceptance of a 10 MW to 14 MW distributed wind farm, compliant to the allocated flicker emission quota.If the rule of thumb does indeed reveal a problem, both passive and active flicker mitigation techniques are proposed such that EMC of the power system is preserved.First and foremost, I would like to thank my supervisor, Prof. Gza Jos, for his continuous guidance and support throughout my engineering master's degree.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".