A Reactive Power Control Scheme for DER-Caused Voltage Rise Mitigation in Secondary Systems
Bibliographic record
Abstract
Distributed energy resources (DERs) are a new class of disruptive technologies with rapidly increasing adoption levels due to favorable government policies and subsidies. However, these emerging technologies come with technical challenges for utilities and system operators; for instance, voltage rise issues in residential secondary distribution systems with high penetration of DERs. One of the low-cost mitigation options to alleviate the overvoltage problem is reactive power absorption. Nevertheless, secondary feeders exhibit a high R/X ratio more noticeably than primary distribution systems, requiring large amount of reactive power for voltage regulation that cannot be entirely provided by the DERs alone. It is also necessary to minimize the reactive power drawn from the primary distribution system to prevent any stress on the network and reduce extra system losses, while at the same time ensuring the voltage within admissible limits. To address these critical issues, this paper proposes a distributed reactive power management, where additional source is provided from inexpensive devices such as switchable shunt reactors. The proposed overvoltage mitigation is accompanied by detailed analytical investigation that estimates the minimum amount of required reactive power to manage the voltage with user specified voltage rise tolerances. Case studies have also been conducted on real residential distribution systems subjected to severe voltage rise issues provoked by large adoption of DERs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".