A Novel Real Time Estimation Technique for Active Unbalanced Distribution Networks Using Smart Meters
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Bibliographic record
Abstract
Estimation of the distribution system voltages and currents is of utmost importance for the network operator to take online decisions. Traditional state estimation techniques require redundant meters readings in addition to pseudo measurements in order to correctly estimate the network states. In order to estimate the network states with few real time measurements, this paper presents a novel real time estimation technique. The proposed technique requires no additional pseudo or virtual measurements for estimation. Moreover, the introduced technique solves the lack of observability problem associated with few measurements. The proposed technique is based on the placement of smart meters at few selected locations; these locations are only dependent upon the network topology and do not change with the injection point of the distributed generators. The proposed algorithm is efficient in dealing with balanced as well as unbalanced distribution networks. The estimation algorithm is implemented and tested on the 69 bus balanced feeder and the IEEE 34 bus unbalanced feeder. The results obtained are compared to the actual load flow results to show the accuracy of the developed technique.
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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) | 0.000 | 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 it