The Impact of Synchronous Generator on Voltage Sag Mitigation in Power System Network
Bibliographic record
Abstract
Power quality (PQ) has become a major concern in recent years. In order to maintain the proper PQ, it is important to detect the PQ problems through fault analysis and investigate for an adequate way to overcome the problems. Sag, which is a sudden decrease in voltage level, is the most common one in PQ problems almost covering 56% of the entire PQ problems. Therefore, mitigation of voltage sag has drawn much attention. This paper represents the effectiveness of synchronous generator in investigation of Voltage Sag Mitigation in Distribution Network. The selected system for this work is the IEEE 14 bus network. The simulation was carried out using MATLAB software. Two possible scenarios, when sag occurrence and the generator connection bus are same and when sag happens near one bus and the synchronous generator is connected to another bus are taken into consideration for simulation analysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".