A Decentralized Wide-Area Voltage Control Scheme for Coordinated Secondary Voltage Regulation Using PMUs
Bibliographic record
Abstract
This paper proposes a novel decentralized purely data-driven Wide-Area Voltage Control (WAVC) scheme for improved coordinated secondary voltage regulation in power systems. To shape the decentralized control structure while accounting for the physical characteristics of the network, Phasor Measurement Unit (PMU) data are leveraged to estimate the electrical distances, conduct the zoning-based partitioning of the network in voltage control zones and decide which buses to choose as the pilot bus locations. The developed PMU-based decentralized WAVC strategy is independent of any system model information, does not require offline training and is adaptive to the available PMU dataset. Dynamic simulations on the IEEE 39- Bus benchmark system verify the effectiveness of the proposed approach under the deployment of the voltage control in one zone as well as the coordination of the voltage control response in a multi-zone system. Due to its data-driven nature, the proposed method can adapt to varying network configurations and topology conditions by updating the voltage control zones and the decentralized control design when required.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".