Voltage regulation in distribution feeders with high DG penetration: From traditional to smart
Why this work is in the frame
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Bibliographic record
Abstract
This paper addresses the negative impacts of distributed generations (DGs) on the utility voltage regulators and hence on the voltage profile of distribution feeders. These negative impacts have been verified through carrying out different simulations on an unbalanced distribution feeder. The results show that a significant regulation problem might arise due to the increased levels of DG penetration correlated with traditional utility voltage regulator's control practices. Consequently, DGs inevitably need to cooperate and communicate with distribution network voltage control devices. Smart grid generally aims to combine the existing utility grids with new digital technology to substantially improve the overall efficiency of the network. In this paper, a communication based multi-agent cooperative control structure has been proposed as a solution to mitigate the voltage regulation issues in distribution feeders with high DG penetration.
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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 | 0.000 |
| 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) | 0.001 | 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 it