PMU configuration for system dynamic performance measurement in large, multiarea power systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Effective assessment of the dynamic performance of the power system requires wide-area information from properly distributed phasor measurement units (PMUs). However, to maximize the information content of the captured signals, the sensors need to be located appropriately, with due account given to the structural properties underlying the given system. In this paper, two numerical algorithms are proposed to achieve this goal. They aim to maximize the overall sensor response while minimizing the correlation among sensor outputs so as to minimize the redundant information provided by multiple sensors. The sensor responses of interest are the bus voltage magnitude, and the angle and frequency coherency indexes, which are estimated by means of a statistical sampling of power system response signals from a transient-stability program. Through the "successive addition" scheme, one of these algorithms easily incorporates mandatory locations such as tie-line busses and large generator step-up transformers. The proposed approaches are first illustrated on the Hydro-Quebec transmission grid and then on a 9-area/67-bus/23-machine test network designed with well-defined geographical boundaries and pre-specified weak interties between electrically coherent areas.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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