Combining Volt/Var & Volt/Watt modes to increase PV hosting capacity in LV distribution networks
Bibliographic record
Abstract
The PV hosting capacity of a LV distribution feeder is directly affected by how much deterioration happens to the feeder power quality as a result of increased PV resources penetration. This paper focuses on the feeder voltage regulation and the use of local voltage control algorithms to improve the issue. Test simulations have been performed on a typical LV distribution feeder with a heavy load demand scenario and another for light load demand. Firstly, no voltage control is being implemented to demonstrate the full extent of voltage limit violation. Then, Volt/Var and Volt/Watt are used individually and afterwards, combining both algorithms is implemented. The results show that overvoltage violation occurs when the feeder is lightly loaded. Volt/Var control lowers the feeder voltage but it does not prevent limit violation. Volt/Watt prevents limit violation but it reduces the hosting capacity considerably. Combing both Volt/Var and Volt/Watt prevents overvoltage violation and improves the PV hosting capacity of the feeder.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".